Download - Reliability from DATA
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Reliability from DATA
A framework for technology
OMDEC
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1. Maintenance / Asset Management Consulting2. Training Programs3. Software Tools4. “Living RCM”5. Canadian Company: Ottawa, Montreal, Toronto,
and Australia Locations
Sample Industries: Mining, Oil & Gas, Utilities, Fleets, Government and Military
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Why collect data? Only one reason: To perform analysis. -
“Reliability Analysis” Why analyze?
To improve the process of maintenance continuously. (CPI = Continuous Process Improvement)
Why CPI? That’s our (i.e. everyone’s, particularly
management’s) job. Why?
Economic survival of the fittest. Keep up with change.
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The “false” promise of CBM technology
Based on the logic that: The more data the better, The faster the better, and The more views (PDAs, iPhone, etc) the better. All of the above are good, but there is a flaw in the
logic.
What is the logical flaw? There is an infinite supply of the wrong data. The logic skirts the question: “What is the right data?”
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What’s the right data? Age (“life”, “life cycle”, “event”) data
Failure Mode occurrences with attributes: event type (PF, FF, S, …), RCM reference, working age
Condition monitoring data relevant to the failure modes of interest.
RCM knowledge of failure modes.
Work orders RCM
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Achieving reliability from data
1. Data extraction and transformation
2. Management of the work order – RCM relationship
3. Sample generation
4. Reliability analysis
Four challenges must be overcome:
Unified EXAKT Process
•Systematic•Quick•Results oriented
Typical focus
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Challenge 1 Data extraction, transformation
Example: FMEA extraction
Example: Work order extraction
Ellipse input
Input from CMMS
Input from CMMS
Input from RCM Cost, RCMO, RCM Toolkit, etc
Output for LRCMOutput for LRCM Data
transformations
Data transformations
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Challenge 2 LRCM …
the most difficult of the four - the key challenge
Text of the selected work order
Text of the selected knowledge record
Event type indicators: PF (blue), FF (red), S (yellow).
Add/Edit KRs (with audit trail)
“Slice and dice”
KPIs
1. Link the work orders and knowledge base.2. Build the knowledge base…
Dynamically,in the day-to-day work order process
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Challenge 3: Sample generation
RCM Knoweldge base
Work Orders that have been linked to the KB
Events table (the sample)
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Sample generation
Work ord. 1, FF RCMREF15
Work ord. 2, FF RCMREF16
Work ord. 3, FF RCMREF16
Work ord. 4, S RCMREF15
Work ord. 5, PF RCMREF15
CMMS Work orders Events table
EF15
B15
EF16
B16
EF16
B16
ES15
B15
EF15
B15
Sam
ple
Right (Temporary) Suspensions:
Legend:
EF: endings by failureES: endings by suspension
Life cycles:
Left Suspensions:
Cal
end
ar T
ime
/Challenge 3 cont’d:
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Challenge 4: Reliability analysis and EXAKT
MaxWSDropet
th
06944.0
1781.0
27092709
781.0)(
Hazard model
+
RULE and Confidence interval
Cost model
EXAKT Decision based on:
Cost and Probability
Decision based on:Probability
RULEScatter
+
Predictive modelPredictive Model
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Challenge 4 - Achieving Reliability from data in EXAKT
Age data (CMMS)CBM dataCost data
Supplied by user
Modeling Software
Intermediate results
Final Result
Cost, Availability,Profitability model
Hazard modelTransition model
RULEMaintenance
Decision
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Challenge 4 - CBM+Simulation in SPAR-PHM
And plan overhaul in 6 months
No maintenance
Replace radio now
Projected worst actor following overhaul
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OMDEC methodology “living reliability”
“on-the-job”IterativeIntegrated
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LRCM Pilot On-the-job process Overcoming Key Challenge 2
1. Monitor work orders & KR links
2. Monitor knowledge record updates
3. Ask questions
4. Propose changes
5. Get feedback
6. Get consensus.
Team
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OMDECLRCM specialists
+Company’s
Engineers, planners, supervisors, technicians
LRCM guidance
Methods,analysesmodels
Knowledge records
Work ordersand KR links
On the job teamwork
Leadership: 1. Recognition,2. Empowerment, 3. Interest
Company’sMaintenanceManagement
Progress reportsKPIs
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OMDEC team participants
Murray Wiseman – LRCM, CBM specialist
Dr. Daming Lin – Maintenance data statistician and reliability expert, signal processing, reliability software, database + ETL specialist.