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.
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.
2.
3.
4.
5.
6.
7.
What are the item’s functions to be conserved? (The
performance requirement)
In what ways can these functions be compromised? (The failure
or failed state)
What causes the loss of function? (The failure mode)
What happens? (The effects)
How does it matter? (The consequences (H, S, O, N)?
What maintenance task should be done to avoid or lessen the
consequences?
What if no appropriate maintenance task can be found?
Introduction - Assertions
1. Without an adequate data sample there can be no
Reliability Analysis (RA)
2. Without analysis there can be no systematic verifiable
improvement in reliability or in operational economy.
Introduction - What is a sample?
CMMS Work orders
Work ord. 1, FF RCMREF15
Events table
EF15
B15
EF16
B16
Work ord. 3, FF RCMREF16
EF16
B16
Work ord. 4, S RCMREF15
ES15
B15
Work ord. 5, PF RCMREF15
Life cycles:
Left Suspensions:
Right (Temporary) Suspensions:
EF, ES: endings by failure, suspension
B: Beginnings
EF15
B15
Sample
Calendar Time
Work ord. 2, FF RCMREF16
Objective
To describe a method wherein
completed maintenance work
orders capture RA enabling
information
Agenda
•
•
•
•
•
•
•
•
•


Introduction
Objective
CBM decisions
The CBM model
The obstacles
The Living RCM solution
Results
Summary
Questions and discussion
CBM Decisions
Three decisions whether to:
1.
Stop the equipment as soon as possible and perform a
specific preventative action as indicated by the monitored
data, or
2.
Schedule an indicated preventative maintenance action
within a specific and safe time period, or
3.
Carry on with the normal operation of the equipment until
the next CBM inspection and evaluation.
Cerrejon´s requirements for CBM
The three criteria
1. Optimal
2. Automated
3. Verifiable
CBM Method: Oil Analysis
Failure mode: General Engine Wear
RULE: 2090 hours
StdDev: 1445 hours
CBM optimal model
Hazard model
0.781 t 
ht  


2709  2709
0.7811
e0.06944MaxWSDrop 
+
Decision based on:
Probability
Predictive Model
RULE and
Confidence
interval
Cost model
Scatter
RULE
EXAKT Decision based on:
Cost and
Probability
The obstacles
There are two possible reasons for the unsatisfactory performance of
CBM 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”
PDF
Low predictability
PDF
f(t)
f(t)
100
Working age t
Working age t
FE
ppm
Weibull Analysis
High predictability
PHM Analysis
Obstacle 1 “ the CBM variable have
no relationship to actual failure
modes”
Non (low) influential indicators
Obstacle 2 Mistaking suspensions
for failures
Misreporting suspensions as failures (or
potential failures) will weaken the model
in two ways:
1.
2.
It will inflate the shape
parameter causing decisions to
be predominantly age based,
regardless of intrinsically good
(predictive) CBM condition
indicators. And,
….
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?
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)
Ellipse - Baseman
Work Order
Event type (FF, FP, S)
RCM
concepts
Free text (updates)
• What I did?
•
What I found?
1. Capturing the right information
in the work orders system (CMMS)
System
RCM as the main language of
Component maintenance.
Function
Failure
Failure
mode
Selecting the Event Type determines the
entire sample point
Living Reliability
Efects
Updates to the RCM
Knowledge base
2. Generating automatically a
sample for RA
3.Motivation, leadership, and
training
An LRCM project implementation succeeds based on a
realization that personnel respond to the intangibles:
1.
2.
3.
4.
Recognition,
Empowerment,
Interest by management in their activities, 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, Availability
2. Costs, and
3. Yield
Low level KPI´s
Low level (leading) KPIs : should measure such indicators as:
1. RCM knowledge added,
2. The number of links between RCM knowledge and work
orders,
3. The number of RA performed
4. CBM performance:
a. Standard deviation in remaining useful life estimation
b. The influence of current CBM variables as reported by
the PHM shape parameter
The managers job
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 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:
% of Satisfactory W.O
Fleet 789C
Today 90%
May
40%
% of Satisfactory W.O
July
70%
Carbones del
Cerrejón
The results achieved
Updates in the RCM knowledge base:
LRCM
FOLLOW UP OF STATISTICS IN RCMCost
FLEET
1
FF
2
FM
F
FF
3
FM
F
FF
4
FUNCTIONS
(F)
FUNCTIONAL
FAILURES (FF)
No. FAILURE
MODES (fm)
F
FM
Haul truck 789C
L1350
Hit EX3600R
98
128
160
153
171
234
694
651
1075
104
129
169
162 739 105 164 748 109 171 785
173 664
243 1201 170 245 1210 174 249 1257
Haul truck 320
Haul truck 240
146
77
193
113
929
466
146
78
193 934 147 195 943
114 468 111 165 692 113 171 723
F
FF FM
Carbones del Cerrejón
Summary
1. Use the language of RCM to guarantee the right information
from the work order system (CMMS)
2. Add the condition monitoring (CBM) data
3. Apply Reliability Analysis to generate optimal DMs.
High
availability
Age data (CMMS)
CBM data
Cost data
Reliability
Analysis
(RA)
Optimal
decision models
Low
cost
More information
Managing LRCM
LRCM KPIs
LRCM and HSE
and
Other related topics
www.livingreliability.com
Questions ?
Thank you for your attention
Do you have any questions?
www.livingreliability.com
oscar.hoyos@livingreliability.com