Slide 1

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 2

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 3

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 4

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 5

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 6

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 7

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 8

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 9

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 10

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 11

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 12

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 13

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 14

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 15

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 16

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 17

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 18

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 19

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 20

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 21

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 22

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 23

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 24

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 25

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 26

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 27

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 28

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 29

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 30

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 31

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 32

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 33

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 34

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 35

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 36

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 37

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com


Slide 38

Using PI for Back Testing UsageBased and Condition-Based
Maintenance Strategies Prior to
Deployment in Asset
Management
Larry Hruby
Basin Electric

Gopal GopalKrishnan, P.E.
OSIsoft, Inc.

Mark Blaszkiewicz
Sebastien Cournoyer, CMRP
DTE Energy

Agenda
• About Basin Electric, About DTE Energy
• History of PI System at Basin Electric and DTE Energy
• History of maintenance systems:
– Basin has Ventyx AssetSuite (aka Indus Passport)
– DTE has IBM Maximo

• Case studies for back-testing:
– Usage-based strategies
– Condition-based strategies

• Q&A
Sebastien Cournoyer, CMRP
DTE Energy

What You Can Expect
• Talk is not product specific – use several tools available
in the PI Infrastructure
• Start with maintenance tasks and work backward to
see if data exists in operations history that can be used
– Collect additional equipment inspection data for proactive
maintenance

• Use PI tools and in-house resources in small
increments without new capital outlay

Coal-fired Power Plant

http://en.wikipedia.org/wiki/Fossil_fuel_power_plant

Basin Electric Power Cooperative
• HQ – Bismarck, North Dakota,
wholesale provider (generation and
transmission) of power to 126 Rural
Electric Systems covering portions of 9
states
• Operate coal, wind, gas, oil based
power generating facilities and a
synthetic natural gas production facility
• Capacity
– 3623 MW (Base load)
– 405 MW (Peaking – CTs)
– 136 MW (Wind)

Basin - Leland Olds Station (LOS)
Fuel:
Lignite with PRB (Powder River Basin)
blending
Unit 1: 220 MW - 1966
Pulverized Coal Boiler (Babcock & Wilcox)
Turbine, GE
DCS, Emerson Ovation 2007 upgrade
Unit 2: 440 MW - 1975
Cyclone boiler (Babcock & Wilcox)
Turbine, Alstom
DCS, Emerson Ovation 2006 upgrade
Under Construction:
Limestone Scrubbers for SO2 capture
($410MM capital project)

Leland Olds, Stanton, North Dakota

Leland Olds Station (LOS)– Software Infrastructure
OSIsoft PI (piloted in 2005)
• 20,000 tags
• Emerson Ovation DCS, Rockwell PLCs, GE relays

Ventyx Asset Suite (previously Indus Passport)
• Started using in 1998 as Passport, has evolved into Asset
Suite in 2008
• Used for Work Management, PM’s, Inventory,
Equipment spec’s & history, Purchasing, Contracts

Leland Olds – Maintenance Initiatives
• Working toward condition based maintenance
(CBM) for years
– Vibration, oil analysis, thermography etc.

• Investigated Rockwell and OSI PI as platform to feed
CBM and operational data to AssetSuite
• PI data reviewed:
–
–
–
–
–

Standard PM work orders usage based
Machine status work order management
Sensor drift and calibration
Control Loop Health
Condition-based notification

DTE Energy – Detroit Edison
Detroit Edison
• Michigan’s largest electric utility with 2.2
million customers
• Over 11,000 MW of power generation
from 7 plants - mostly coal fired
• 54,000 GWh in electric sales
• $4.7 billion in revenue

DTE Energy - Detroit Edison

DTE - Plants and Performance Center

Monroe – 3,135 mw

Belle River – 1,260 mw

Harbor Beach – 103 mw

Trenton Channel - 730 mw

Performance Center – 11,588 mw

St Clair – 1,417 mw

River Rouge - 527 mw

Greenwood – 785 mw

Fermi – 1,100 mw

DTE – History of PI and Maximo
• PI is a key infrastructure and technology enabler for
real-time operations data as part of the “Enterprise
Business System” at DTE
Additional details from a Nov. 2008 presentation at:
www.osisoft.com/osisoft/downloads/Regional_Seminars/Detroit/DTE%20Energy%20(John%20Kapron).pps

• IBM-Maximo is a key application for work management as part of
the “Enterprise Business System” at DTE
Additional details at:
http://www-03.ibm.com/press/us/en/pressrelease/21649.wss

DTE – Details of PI usage
• In use since 1998 –
started with a pilot at
Monroe in 1998
• Enterprise Agreement for
corporate wide use
• PI is an infrastructure
product – magnitude of
use and functionality is
expanding

Success!

DTE - Total Fleet Management
Drives Performance Excellence
Process Costs
Asset Health
Operational Performance
Market Value
Fleet Optimization

Financials
Work Management

Market

SAP
Maximo

MISO,
Fuel Coat Framework
Unit Capacity Framework

Real-time
Process Applications
Expert Systems

SME Status Displays
WEB Portal
Applications
Distributed Control Systems (DCS)
Distributed PI Historians

DTE - Control & Technology Framework
People
Fossil Generation
Business Unit Strategy
Actionable
Information – KPI’s

Making right decisions when it matters!
Drives Performance Excellence
Fleet
Optimization
Process Costs
Asset Health,
Market Value

Fleet Optimization
Process Costs, Asset Health,
Reliability
Operational Performance, Market Value

15%

Relate all Data Sources

Business Intelligence

ProcessNet Framework
Outage & De-rate (UCF)
(PI, ProcessGuard, Maximo, SAP, UCF, P3M,
Maintenance & Market 25% Predictive Monitoring, NeuCo, LIMS, Plant View ..)

Advanced Analysis & Process Optimization

Expert Systems

Reliability Academy

Predictive Monitoring, Optimization
MBO/PdM/Risk Assessment 60%

Equipment, Process, Performance, Reliability Models
Closed Loop Process Optimization

System Dashboards
Fleet Status Assessment

Fleet Drill down
90%

Subject Matter Experts

WEB Visualizing

Standard User Interface

Plant Alarm, DCS Real-time WEB Graphics

WEB Visualization

Easy Access to Information

100%

Process Discrete Data
Engineering Applications

Engineering Applications
PMAX, Digital Fuel Tracking, Fuel Cost Framework

Process Discrete Data
Discrete data
Limited value

ABB

90%

Post Event Analysis

Distributed Control Systems (DCS)
Distributed OSIsoft PI Historians

Large Population of Data

RFID, PMAX, DFTS, eNote,
Fuel Cost Framework,
Alarm Management

DCS, PLC & PI
90%

% Complete

Link Operations and Maintenance
• Business goals
– Usage based maintenance (UBM) strategies
• Mostly, data is already in PI

– Condition-based maintenance (CBM) strategies
• When relevant data not in PI, collect equipment inspection
specifically designed to drive maintenance benefits

• Business justification
– Calendar-based maintenance strategy := Amount of
maintenance will be same as last year
– UBM and CBM:= Opportunities for savings
– Use PI history and Maintenance history to:
• Back-test calendar based PM for conversion to UBM
• Back-test corrective work order (CM) events for conversion
to CBM

Usage-based Criteria
• PI totalizer

• Run-hours -

• PI time-filtered conditional expressions
(time-weighted and event-weighted)

– Coal feed conveyor
– Pulverizer
– High pressure service water pumps

• Run-modes - number of starts, number of
trips – Peaker CT blades
• Run-weight - tonnage processed (mining
industry), flow-rate (time-integral) converted
to volume

Service Water Pump – Usage Based
Pumps were off for extended period, however the PM WO still went
out - 28 PM hours

Fuel Conditioner – Usage Based
Equipment runs about 80% of total year; usage based
maintenance can save 152 PM hours

Coal Conveyor - Usage Based
Maintenance: 60 PM hours per conveyor per year; 22 conveyors per site, 6 sites
Actual runhours: 25% based on PI data, implies a 75% savings
Projected savings: 900+ PM hours (approx. $45,000 at $50/hr) per year per site

Pulverizer - Usage Based
Maintenance: 160 PM hours per pulverizer per year; 16 pulverizers per site, 6 sites
Actual runhours: 80% based on PI data, implies a 20% savings
Projected savings: 480+ PM hours (approx. $25,000 at $50/hr) per year per site

Condition-based Criteria
• Equipment failure is known to be correlated to a
slowly degrading metric that can be monitored
– Temperature (Motor windings, Bearing)
– Pressure or DeltaP (heat-exchanger plugging, filters)
– Vibration – Amplitude, FFT etc. ; Also interpret along
with operations data in PI

• Instrument and transmitter calibration
• Control loop health

Secondary Air Heater Plugging
Air heater tube plugging causes DeltaP (green line)
to increase over several months and is a trigger for
maintenance

Boiler (convection section) Tubes - Plugging
Rapid rate of change of Delta P over several days
is a trigger for maintenance

Steam Condenser Fouling
Steam condenser fouling causes condenser
pressure to rise (blue line), note the rapid rise in a
matter of few days. Threshold is 4 inHg.

Green line shows the inlet water temperature which
is relatively constant

Vibration – Conveyor Motor
- Note the rapid rise in vibration amplitude in Jan.
and Feb.; also shown in the trend.
- Resolved by a shaft re-alignment – see next slide

Vibration – Conveyor Motor
Shaft realignment resolves the vibration issue

Instrument Drift – O2 Analyzer – U2-E
Based on redundant dual sensors

Transmitter Drift
Boiler feedwater pump discharge pressure
Based on redundant triple transmitters (PressA,
PressB and PressC)
Good

XY Plot, PressA (X) vs. PressB (Y1), PressC(Y2)

Not Good

Transmitter Drift – U1 – Spray Flow
Green – Delta between the transmitters
Blue – Unit 1 is at about 220 MW

Firing Rate Control Loop – Boiler Exit O2
O2 set point: Approx. 3.2%
Actual process value (green line): Varies from 1% to 5.5%

Firing Rate Control Loop – See Notes
At purple crosshair, air (red) peaks when coal (yellow) dips causing
O2 (green) to peak after 30-40 secs.
At white crosshair, air (red) dips when coal (yellow) peaks causing
O2 (green) to fall below 1% after a lag of 30-40secs, and so on….

Manual Inputs – Operator Rounds in PI
Equipment inspection data collection specifically designed to help maintenance
tasks (data not already in PI)
Benefits: Proactive maintenance for increased MTBF (mean-time-between-failure)

Source:
www.aeec.com/conveyor/Belt_Cleaners/Vplow.
aspx (retrieved Jan 2009)

Operator Rounds: V-PLOW status on a coal conveyor belt

Breaker Inspection Sheet
Equipment inspection data specifically designed to help with maintenance
tasks (data not already in PI)
Data collection includes numeric values such as resistance, clearance etc.

Manual Inputs – Operator Rounds in PI
Equipment inspection data specifically designed to help with
maintenance tasks (data not already in PI)
Everything we visually inspect, measure or observe can be recorded in PI
to track, trend and monitor
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•

Breaker inspection – 80 attributes per breaker, 1000 breakers – annual inspection or after a trip
Dust Collector
Screw conveyor
Electric motor
Reducer
Bearings
Transfer point / chute liner condition
Limit-torque actuator
Hydraulic cylinder, Pneumatic cylinder
Pumps
Mechanical seals
Conveyor skirting
Conveyor scraper, primary and secondary
Idler, roll assembly
Pulley
Lube system
Coupling
Torque coupling
Valve
Piping

Findings
• Operations history and maintenance history can validate and
quantify benefits for usage-based criteria prior to deployment
• Use manual input data (Manual Logger) to supplement conditionbased strategies
• Review control loops, including the instruments, transmitters and
calibrations
• Vibration data – combine with equipment operating conditions
for better diagnostics

Enterprise Gateway
SOA (service oriented architecture) to exchange information
between the PI System and any external system via web services.

Questions?

Thank you

www.osisoft.com