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Reliability from DATA. A framework for technology OMDEC. Maintenance / Asset Management Consulting Training Programs Software Tools “Living RCM” Canadian Company: Ottawa, Montreal, Toronto, and Australia Locations - PowerPoint PPT Presentation
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Reliability from DATA
A framework for technology
OMDEC
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
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.
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?”
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
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
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
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
Challenge 3: Sample generation
RCM Knoweldge base
Work Orders that have been linked to the KB
Events table (the sample)
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:
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
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
Challenge 4 - CBM+Simulation in SPAR-PHM
And plan overhaul in 6 months
No maintenance
Replace radio now
Projected worst actor following overhaul
OMDEC methodology “living reliability”
“on-the-job”IterativeIntegrated
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
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
OMDEC team participants
Murray Wiseman – LRCM, CBM specialist
Dr. Daming Lin – Maintenance data statistician and reliability expert, signal processing, reliability software, database + ETL specialist.
