Transcript TDC Downtime Data Sources - Association for Facilities

Business Industrial Network
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True Downtime Cost
Data Sources (Definition:)
TDC – True Downtime Cost
•A method of recording and analyzing all significant cost
metrics associated with equipment downtime in a building
or manufacturing facility.
•TDC provides a way to assign time and/or monetary value
to previously considered “non-tangible” cost of downtime.
•Also TDC includes downtime factors commonly overlook to
arrive at a more true value for the cost of downtime.
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Data Sources Overview
Data – too much of it, not enough of it,
inadequate quality or the wrong sort:
and what is it used for anyway?
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Considerations of best metrics:
What you measure is what you’ll get!
 Ultimately must be able to accurately track
failure rates and allocate costs
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individual machines (location, asset)
machine categories (motors, pumps)
components (bearings, seals)
Major benefits can be attained with current
technology -- more effectively applied
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lower cost data collectors
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Digging for data
 equipment
histories,
 CMMS reports,
 life cycle cost analyses,
 financial records,
 production schedules.
These are the recommended sources to build a cost
justification report to be presented to the bean counters.
A maintenance manager would need a full time research
assistant to run a productive department.
Measurement effectiveness:
 Do
measures such as maintenance cost
/ RAV show contribution to real
objectives?
 age
of equipment, process intensity
 MTBF;
total population / total repairs or
equipment specific statistics

which, what, how often
 PM
compliance and PM backlog, %
overtime, % PM compared to % reactive
 don’t
measure whether activity is required
or how much value is produced
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What do all these data sources
have in common?
 They
all build on downtime cost
estimates that are only 10% or less of
the True Downtime Cost. (10%TDC)
 Cost justification requires analysis of
several of these areas by management.
 Often you have to justify the validity of
the data source.
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Where does valid data come
from?
 all
computer systems and networks
 plant automation systems
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distributed control systems
programmable logic controllers
diagnostic monitoring systems.
 asset
management software
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How to bring it all together
 Wonderware
 Versacall
The new millennium focus is on bringing the valid
data from various sources back to the management
software and technique of your choice.
Will this full circle of data management bring us
close to 100% management efficiency?
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Versacall.com
 VersaCall
Facility Communications
System.
 capture
and document downtime
 monitoring response time
 communicating an alarm occurrence
"5% of cost in a sites production capability from
downtime is a fairly safe number. It does vary by
industry ~ mostly going up from the 5%."
"80% of the manufacturing operations I have
interacted with have no idea what they are losing in
true dollars with downtime."
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Not even close
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You will see a 200%
to 300% increase in
efficiency, but that’s
only 30%TDC, will
that give you the
required ROI?
 Why settle for 300%
when you can easily
have 800%?
“LEAN”
TPM, RCM, PM
OEE,RAV
ERP,CMMS,EDI,DCS,PLC
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The Answer, TDC
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Actually a combination
of two methods are
used to bridge the gap
between data collection
and management
technique.
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Strict usage of TDC
metrics
And data sharing
standards like MIMOSA
“LEAN”
TPM, RCM, PM
TDC
ERP,CMMS,EDI,DCS,PLC
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Maintenance Management
Condition Measurements
Decision Support
Data
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
Maintenance Management
Condition Measurements
Start/Stop
Speed
times
Decision Support
fluid
(lube oil) condition
vibration (on and off-line)
operating measurements
(on-line and operating logs)
motor characteristics
Data
thermography
anodic/cathodic voltage
ultrasonic (leak detection)
corrosion thickness
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
Maintenance Management
Condition Measurements
Data
Data:
ID’s: Plant / Location / Equipment
Events
Numerical values (measurements)
True Downtime Cost Metrics
Measurement trends
Array / Image:
•Vectors
•Time Waveforms
•Orbits
•Spectra (frequency, order, CPB)
•Lube oil particle
•Temperature images
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
Maintenance Management
Condition Measurements
asset
Data
management (inc. spare parts)
workforce management
scheduled maintenance (inc. PM)
work management
MRO inventory management
tool and rental equipment
cost accounting
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
Condition Measurements
Maintenance Management
From Maintenance Management:
Conditions found
Spare parts availability
Work accomplished -- Action taken
Maintenance history: work performed, cost,
process downtime
Data
Nameplate data
Manufacturers specifications
Work order issued: Work order number,
requirements: parts, resources, tools, people
Work schedule
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
Maintenance Management
Condition Measurements
mechanical
diagnostics inc. rolling bearing
performance/efficiency
reciprocating analysis
operating deflection shape (ODS)
Data
root cause
reliability centered maintenance (RCM)
risk
prognosis
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
Condition Measurements
Maintenance Management
Information
Status -- something happened, event
State of health -- numerical condition index
Rate of change (health/severity) -- numerical
Data
Time to action -- predicted date under current conditions
Problem identification -- description
Components affected -- description
Recommendations -- operating and maintenance
Remarks/Comments -- explanatory information
Work request -- yes or no
Confidence -- numerical
Information
MIMOSA
Equipment Management
Control System - DCS
Information Model
thanks to: Ken Bever, John Hawkins, Alan Johnston, Art Jones, Peter Morgan
MTBF Example
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Average 2 year MTBF on 2,000 pumps
(compared to world class -- 6 to 7 year)
 Average cost of repair $5,000
 Double MTBF to 4 years
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6 year MTBF
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saves $3.3 million
That’s at the profit level!!
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saves $2.5 million!!
how much product must be produced to deliver $2.5
million profit at 10% pretax??
PROFIT CENTERED MENTALITY
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Information Sources
Information required for equipment
management is optimally developed
within specialty systems:
condition monitoring / assessment
Start/Stop, speed, vibration, fluid analysis,
thermography, motor electrical, ultrasound
control (DCS)
performance, efficiency Calculated with TDC
maintenance management (CMMS)
manufacturers specifications, task instructions,
history, parts, costs
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Information must be:
 Readily
available, easily exchanged and
clearly understandable for everyone with
requirements throughout the enterprise
MIMOSA!
Machinery Information Management Open Systems Alliance
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TDC Metrics
 Equipment
Metrics
 Labor Constants
 Downtime Data
 Outsourcing Information
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TDC Details
Equipment
Categories
People
Labor
LPP/M
Downtime
Time
Reduced
QC
Scrap
Product
Maintenance
Band-Aid
Start-Up
Bottleneck
Sales Exp
Engineering
OEM
Tooling
Management
Overhead
Part / Ship
TDC, a closer look at
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Categories
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Electrical surge cost, Set up, % reduced till start/stop
Equipment fatigue
Scrap produced, is it recycle able
Bottleneck
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Cost per unit at that stage in production
Units per hour
Start-Up
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Number of Direct and in-direct idle workers
Product
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Use MIMOSA, machine, priority, type, cell, line, Notes, etc.
People
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Equipment
List other downstream equipment, and % effected
Expected Sales
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% effect on product out the door.
TDC, a closer look at
 LPP
/ Equipment Contribution
 Not
 QC
Labor
as accurate, use if not items below
wages
 Extra
inspections, Rework
 Management
wages
 Engineering
 Maintenance
 Support
 Equipment
operators
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TDC, a closer look at
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Time Down
Reduced
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Annual fee/ est. hours used per year, or T&M + Expenses
Tooling
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Is a sub category of several, value in %TDC
OEM
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Number of units, % recovered by recycling
Band-aid
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% reduced, for how long
Scrap
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Downtime
Replacement, reworking, recycling
Parts
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Actual repair, and band-aid
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TDC-Warning Data Overload!
Too many variables, Too complicated, Too much change!
Equipment
Labor
Downtime
Overhead
These are all one time entry of
constants, updated annually, exported
from your existing computer systems.
These are per downtime occurrence entries,
but most can be exported from your CMMS.
You can use a percentage of existing
numbers depending on amount of TDC
metrics they are made up of
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Is using TDC too much change ?
Not really. You just need to require up front
that your vendors adhere to MIMOSA
standards and TDC metrics.
Your vendors being data collection equipment
vendors, and software vendors such as
CMMS.
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Let’s put Downtime in it’s own bucket
and make sound decisions.
DT veiwed now
0%
2%
WITH TDC
1%
1%
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6%
TDC represents the final
bottlenecks to a fully integrated
and auditable approach to
“LEAN”
maintenance strategy
TPM, RCM, PM
development / justification.
TDC
Click the link to learn more about
•TDC Data Source
•TDC Cost Factors
ERP,CMMS,EDI,DCS,PLC
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