STLE 2012 CBM and Reliability Engineering Conference “Achieving Reliability from Data” at Cerrejón A Living Reliability Centered Maintenance (LRCM) project Gerardo Vargas, Carbones del Cerrejón Ltda. Juan Carlos Consuegra, Carbones del Cerrejón Ltda. Oscar Hoyos Living Reliability (presenter) Murray Wiseman, OMDEC Inc. Dr. Daming Lin, OMDEC Inc.
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STLE 2012 CBM and Reliability Engineering Conference
STLE 2012 CBM and Reliability Engineering Conference. “Achieving Reliability from Data” at Cerrejón A Living Reliability Centered Maintenance (LRCM) project. Gerardo Vargas, Carbones del Cerrejón Ltda. Juan Carlos Consuegra, Carbones del Cerrejón Ltda. - PowerPoint PPT Presentation
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STLE 2012 CBM and Reliability Engineering Conference
“Achieving Reliability from Data” at CerrejónA Living Reliability Centered Maintenance (LRCM) project
Gerardo Vargas, Carbones del Cerrejón Ltda.Juan Carlos Consuegra, Carbones del Cerrejón Ltda.
Oscar Hoyos Living Reliability (presenter)Murray Wiseman, OMDEC Inc.
Dr. Daming Lin, OMDEC Inc.
Introduction – Main Actors
•Carbones del Cerrejón – World´s largest export coal mining operation
•OMDEC – EXAKT CBM Optimizing Software
•Living Reliability – Consultants in Living RCM (LRCM)
Commonly used terms
• LRCM: Living Reliability Centered Maintenance• CMMS: Computerized Maintenance Management System• Event type: How a failure mode’s life cycle ends? By:
Potential Failure (PF)Functional Failure (FF)Suspension (S)
• PHM: Proportional Hazard Model. Extends Weibull to include CBM data.
• CBM: Condition Based Maintenance
RCM
1. What are the item’s functions to be conserved? (The performance requirement)
2. In what ways can these functions be compromised? (The failure or failed state)
3. What causes the loss of function? (The failure mode)4. What happens? (The effects)5. How does it matter? (The consequences (H, S, O, N)?6. What maintenance task should be done to avoid or lessen the
consequences?7. What if no appropriate maintenance task can be found?
The three criteria1. Optimal2. Automated3. Verifiable
CBM optimal model
Predictive Model+
Hazard model
MaxWSDropet
th
06944.0
1781.0
27092709
781.0
RULE and Confidence interval
Decision based on:Probability
RULE
Scatter
Cost model EXAKT Decision based on:
Cost and Probability
The obstacles
There are two possible reasons for the unsatisfactory performance ofCBM decision model.
1. The condition monitoring variables that are available to the CBM program intrinsically bear little or no relationship to the actual failure modes that occur in the fleet. Or,
2. The data sample used to build the predictive model does not distinguish between Failure and Suspension.
Obstacle 1 “ the CBM variable have no relationship to actual failure modes”
Low predictabilityLow predictability
Working age t
PDF
f(t)
Weibull Analysis
FEppm
100Working age t
PDF
f(t)
High predictabilityHigh predictability
PHM Analysis
Non (low) influential indicators
Obstacle 1 “ the CBM variable have no relationship to actual failure modes”
Misreporting suspensions as failures (or potential failures) will weaken the model
in two ways:
1.It will inflate the shape parameter causing decisions to be predominantly age based, regardless of intrinsically good (predictive) CBM condition indicators. And,2.….
Obstacle 2 Mistaking suspensions for failures
2. It will increase the scatter, and consequently confidence in prediction.
This point raises a subject that RCM stresses as one of prime importance. What shall be the “standard” used to declare failure?
Obstacle 2 Mistaking suspensions for failures
The Living RCM solution
1. Capturing the right information in the work orders system (CMMS)
2. Generating automatically a sample for RA
3. Motivation, leadership, and training
4. Low and high level performance metrics
1. Capturing the right information in the work orders system (CMMS)
Work Order
RCM concepts
Ellipse - Baseman
Free text (updates)•What I did?
•What I found?
Event type (FF, FP, S)
Living Reliability
SystemComponent
Function
Failure
Failure mode
Efects
RCM as the main language of maintenance.
Updates to the RCM Knowledge base
1. Capturing the right information in the work orders system (CMMS)
2. Generating automatically a sample for RA
An LRCM project implementation succeeds based on a realization that personnel respond to the intangibles:
1. Recognition, 2. Empowerment, 3. Interest by management in their activities, and 4. Training.
3.Motivation, leadership, and training
4. High and low KPI´s
• Performance metrics should point us precisely to what we need to improve currently in our maintenance process.
• That is, they should trigger a control action. Subsequently they should confirm and measure the extent to which the control action had the desired
effect.
4. High level KPI´s
High level (lagging) KPIs : provide, at various levels of granularity, such measures as:1. MTTF, MTTR, Availability2. Costs, and3. Yield
Low level KPI´s
Low level (leading) KPIs : should measure such indicators as:1. RCM knowledge added,
a. Standard deviation in remaining useful life estimationb. The influence of current CBM variables as reported by
the PHM shape parameter•The number of links between RCM knowledge and work orders,•The number of RA performed•CBM performance:
It is the manager’s job to set low level objectives that:1.Employees can influence by the way they perform their duties, and that
2.Support the high level organizational targets.
The managers job
The results achieved
1. Better analysis (lower shape factor, lower standard deviation ) More confidence in making decisions
2. The maintenance personnel have now a method to register in a precise way the right information inside the W.O. system.
3. More Reliability Analysis
4. Develops, verifies, and continually improves optimal maintenance policies
5. Updates to the knowledge base
The results achieved
Improvement in the quality of the information required for RA: