Technology to Support the Increasing Focus on Asset Reliability January 29, 2004

Agenda • About Ivara • Case study of focusing on reliability • Industry trends • Technology for improved reliability

About Ivara • • Ivara provides solutions to maximize asset reliability – – Unique reliability software Unparalleled reliability expertise Our solution helps customers to – – – Optimize asset performance Improve quality and customer service (in manufacturing) Ensure safety and environmental integrity – Identify

The Right Work at the Right Time

Customers •

Oil and Gas

– – – – – – – – – Terasen Pipelines Citgo Global Sante Fe Helmerich & Payne Drilling Noble Drilling Parker Drilling Rio Alto Exploration Syncrude Chevron Canada •

Utilities & Power Generation

– – – – – EPCOR New Brunswick Power Southern California Edison Pacific Gas & Electric Brighton Beach •

Food and Beverage

– – Kraft Molson Breweries • • •

Pulp & Paper

– – – – Domtar Alberta-Pacific Forest Products Slave Lake Pulp The Price Company

Metals and Mining

– – – – – – – – – Gallatin Steel Alcan Smelters and Chemical Algoma Steel Dofasco de Mexico Barrick Goldstrike Inco North Star Steel Cargill Salt Quebec Cartier Mining Co.

Facilities and Fleets

– – Gibson Petroleum Transportation TSI Delta Port

Case Study - Dofasco • North American Manufacturer • $3 Billion / Year in Revenue • Manufacturing Equipment Replacement Value of $5 Billion

Motivation to Improve • Business performance reached a plateau in the late 1980’s • Dramatic external changes began to take hold in the market place • Forcing a need for internal response to these external changes

Motivation to Improve • Equipment Reliability identified as the key to improvements in: – – – – Product quality Production output Costs Shareholder return

The Results 100 % % Total Maintenance Hours 30% Proactive Maintenance 80% 70% Then Reactive Maintenance 20% Now

The Results 100 % Average Equipment Availability

22%

Unavailable

9%

78% 91% Available Then Now

The Results Quality increased from 76% yield to 91% 90 % Prime Yield 85 80 75 70 Then Now

The Results Market pressures to reduce costs demanded significant downsizing 12,500 # of Employees 7,000 3,460 Maintenance employees 1,700 Maintenance employees Then Now

The Payoff • • • • Most Profitable North American producer in their sector Ranked as #1 worldwide manufacturer in their industry by Dow Jones 2 years running North American benchmark for World Class maintenance practices and technologies Winner of two prestigious maintenance awards: – – Best use of Innovation and Technology in Maintenance Best Maintenance for a Large Plant

Industry Trends • Leaders are Focusing on Reliability – After 20 years of CMMS experience Changing Demands Better Understanding of Equipment Behavior New Technologies & Practices

The Traditional View of Failure Assumed most items wear out at about the same age Conditional Probability of Failure Age Preventive Maintenance (time based)

The View of Failure Evolved Probability of Failure Age The PM itself could cause failure

The Reality of Failure • There are six failure patterns <20% time based 4% >80% random 7%

Bathtub

2%

Condition Related

14%

Age Related Random Failure

5% 68%

Fatigue Related Infant Mortality

The majority of failures are random, not time-based

Technology for improved reliability • How is work identification software (such as Ivara EXP) different from a traditional CMMS?

• Where does it fit in?

CMMS: Focus on Efficient Work Execution Crafts / Trades people Shutdowns Schedules Areas The Maintenance Function

EXP: Focus on Work Identification – Doing the Right Work Crafts / Trades people Shutdowns Schedules Areas The Maintenance Function

Leverage Existing Technologies Process Control Tools  SCADA  Data historians

CMMS

Predictive Maintenance Tools  Check sheets  Hand held devices  PdM/CBM technology  Asset Management  Work Order Management  Planning & Scheduling  MRO Materials  Procurement  Tasks and Jobs  Personnel & Trades

Leverage Existing Technologies Process Control Tools  SCADA  Data historians

CMMS

Predictive Maintenance Tools  Check sheets  Hand held devices  PdM/CBM technology  Asset Management  Work Order Management  Planning & Scheduling  MRO Materials  Procurement  Tasks and Jobs  Personnel & Trades

Leverage Existing Technologies Doble analysis Infrared thermography Oil analysis Circuit breaker analyser results Relay calibration tests RCM analysis Aladon tool kit Operator rounds Visual inspections Electrical/Mechanical inspections

Work identification software

 Applied RCM  Condition-based management  Rules-based diagnostic engine  Indicator-based job triggers  Performance analysis and tracking

The Right Work at the Right Time

Leverage Existing Technologies Process Control Tools  SCADA  Data historians

CMMS

Predictive Maintenance Tools  Check sheets  Hand held devices  PdM/CBM technology  Asset Management  Work Order Management  Planning & Scheduling  MRO Materials  Procurement  Tasks and Jobs  Personnel & Trades

Leverage Existing Technologies Process Control Tools  SCADA  Data historians

CMMS

Predictive Maintenance Tools  Check sheets  Hand held devices  PdM/CBM technology

Work identification software

 Applied RCM  Condition-based management  Rules-based diagnostic engine  Indicator-based job triggers  Performance analysis and tracking  Asset Management  Work Order Management  Planning & Scheduling  MRO Materials  Procurement  Tasks and Jobs  Personnel & Trades

How Work Identification Software Works  Set up Indicators Define equipment performance targets   Normal Non-normal    Collect & Input Readings Manual check sheets Electronic check sheets On-line data EXP Analyses & Presents Results  One place to view the health of all equipment  Draws attention where needed Right Work sent to CMMS  CMMS executes

The Right Work at the Right Time

Set Up Indicators Set up Indicators  Define equipment performance targets  Normal  Non-normal

Set Up Indicators

Set up Indicators • Indicator types – – – – Descriptive (v-belt cracked, noisy bearing) Numeric (pressure, temperature) Calculated (wear rate, efficiency/effectiveness) Rule-based (combination of the above) • Indicators can be linked to suggested corrective work

Define Performance Targets • Normal and non-normal indicator values – specific to asset operating context • Assign alarm severity to non-normal values Oil Viscosity Critical Warning Normal 10 50 100

Descriptive Indicators

Numeric Indicators

Calculated Indicators

Rules-Based Indicators

Collect & Input Readings Set up Indicators Collect & Input Readings  Define equipment performance targets  Normal  Non-normal  Manual check sheets  Electronic check sheets  On-line data

Collect & Input Readings • • Collection methods – – Manual • Paper check sheet Electronic • Handheld check sheet, online data sources Input methods – – Manual • Keyboard Electronic interface • • Upload handheld data Poll online data sources

Handheld Data Collection

Integration to Online Data

Work Identification Software Analyses & Presents Results Set up Indicators Collect & Input Readings EXP Analyses & Presents Results  Define equipment performance targets  Normal  Non-normal  Manual check sheets  Electronic check sheets  On-line data  One place to view the health of all equipment  Draws attention where needed

• Analyses & Presents Results Compares current asset condition to performance targets • Analysis is automated – No manpower needed • Results are presented graphically

Analyses & Presents Results

Analyses & Presents Results

Analyses & Presents Results

Analyses & Presents Results

Right Work Sent to CMMS  Set up Indicators Define equipment performance targets   Normal Non-normal    Collect & Input Readings Manual check sheets Electronic check sheets On-line data EXP Analyses & Presents Results  One place to view the health of all equipment  Draws attention where needed Right Work sent to CMMS  CMMS executes

The Right Work at the Right Time

CMMS executes

The Right Work at the Right Time

• Manual interface – Alarm acknowledgements can be manually transferred to your CMMS – – CMMS work document recorded in Ivara.EXP

Acknowledgement step turns off alarm • Automatic interface – Feeds CMMS with suggested work • CMMS performs Right Work at Right Time

Right Work Sent to CMMS

Software demonstration