rcm applied to achieve best life cycle
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Filename: RCM-Applied-to-Achieve-Best-Life-Cycle.pdfTRANSCRIPT
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Dr Bill Wessels PE CRE Principal Research Scientist
Reliability & Failure Analysis Laboratory http://rfal.uah.edu
Reliability Centered Maintenance Applied to Achieve Best Life Cycle Costs
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Dr Bill Wessels PE CRE Experience:
• 1975 – 1989 Tramp Engineer, mining mobile machinery & process equipment life-cycle sustainability
• 1989 – 2005 Contractor [Biomedical Devices, DoD and NASA] design-for- reliability, RCM
• 2005 – Research in design-for- reliability & life-cycle sustainability for mechanical and structural components
Credentials • BS USMA, West Point ’70 • PhD Reliability Systems Engineering, UAHuntsville ’96 • PE MechE, Pennsylvania, ‘82 • CRE, ASQ, ’96
Author – Practical Reliability engineering and Analysis for System Design and Life-Cycle Sustainment, CRC Press, 2010
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Introduction
Reliability-centered maintenance serves to preserve system functionality by performing scheduled maintenance actions that prevent unscheduled system downing events during scheduled operations
RCM achieves its objective by developing an understanding of critical part failure
Understanding part failure is manifested by the ability to measure the consumed life of a critical part
Scheduled maintenance is defined by application of a risk threshold to the consumed life
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RCM Roadmap
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Part Cost Objective Function· Labor Costs· Materials Costs· Overhead Costs
Logistics Downtime
Math Model
Spare Strategy
Math Model
PreventiveMaintenance Math Model
Resource Queuing
Math Model
PartReliability/Cost
Simulation
Assembly Reliability/Cost
Simulation
System Reliability/Cost
Simulation
PartFailure
Math Model
PartRepair
Math Model
Part ReliabilityLife-Cycle Affordability
Assembly ReliabilityLife-Cycle Affordability
System ReliabilityLife-Cycle Affordability
Condition Indicator
Time-to-Failure Reliability Failure
Math Model
CBM
TDM
SDMStress-Based
Reliability Failure Math Model
Single Fail MechSingle Fail Mode
f(t)
Y
E
S
Y
E
S
YES
NO
PartFailure Mode
Multiple Fail MechMultiple Fail Mode
f(s)
NO
Metric: Part Condition Indicator
Metric: Part Time in Service
Metric: Part Stress Profile
RCMDatabase
System
Subsystem
Critical Items List
Assembly
Part
ORFunctional
Failure
PartPart
RCMDatabase
Part Failure Consequences
Analysis
Perception of Part Failure
P-F Interval
Operator
Maintainer
Criticality A
nalysis
ORFailureMechanisms
FailureModes
PhysicalStress
ThermalStress
EnvironmetalStress
Change in Shape
(Strain)
Change in Geometry(Crack)
Change inMaterial Property
(Corrosion)
OR
Critical Items List
RCMDatabase
Part
FailureMechanisms
Sources
Transportation Storage Function
Operational Ambient
OR
OR
PartFailure Effects
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Part Reliability- Maintainability Cycle
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System Downtime
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Source of RCM Cost Benefit
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Part failsSystem down
Maintenance action initiated
Wor
k S
tart
s
Time
Time-to-Repair
post-Repair Logistics Downtime
pre-Repair Logistics Downtime
$Lost Opportunity
$Labor$Overhead
$Labor$Materials$Overhead
Wor
kRe
sum
es
$Labor$Overhead
$Benefit
Part failsSystem down
Maintenance action initiated
Wor
k S
tart
s
Wor
kRe
sum
es
$Labor$Overhead
$Labor$Materials$Overhead
Time
Time-to-Repair
post-Repair Logistics Downtime
pre-Repair Logistics Downtime
$Lost Opportunity
Total Downtime
$Labor$Overhead
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Top Level RCM Path Develop a rank ordered critical items list – CIL Perform reliability failure analysis to identify:
• Sources of failure mechanisms (Conditions of use) • Failure mechanisms action on the critical part (Cause of
part failure) • Failure modes (Damage to part) • Failure effects – part (Symptoms of the damage) • Failure effects – assembly (Consequences of part
failure)
Select appropriate RCM Path • CBM • TDM • SDM
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Condition-Based Maintenance CBM
Consumed life characterized by a condition that defines the failure mode/damage • Change in shape • Change in geometry • Change in material properties
Method for investigating the damage, NDI • Visual inspection of condition indicator • Manual measurement of condition indicator • Sensor measurement of condition indicator
Metrics that characterize the damage Risk Threshold
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Notional Linear CBM Concept
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Notional CBM Concept
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Decreasing Condition Indicator
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Diverging Condition Indicator
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Diverging Condition Indicator
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Converging Condition Indicator
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Converging Condition Indicator
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Fatigue Condition Indicator
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Fatigue Condition Indicator
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Step Condition Indicator
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Step Condition Indicator
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Notional Attribute CBM Concept
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Time Directed Maintenance, TDM
Consumed life characterized by time in service, but…
Single failure mechanism with single failure mode
Failure mode correlated to operating time
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Time-to-Failure Data
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Time-to-Failure Histogram
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Fit Data to 3-Parameter Weibull Median Ranks Regression
First: Fit the 2-Parameter Weibull
Then: Select a value for the location parameter, g
• Choose the mid-time between 0 and Tmin
• Calculate Xg = Xi – g
• Calculate r2 for Xg & Y
If: r2 for Xg < r2 for the 2-Parameter Weibull, use the 2-Parameter Weibull
If: r2 for Xg > r2 for the 2-Parameter Weibull,
fit the 3-Parameter Weibull
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Fit Data to 2-Parameter Weibull Median Ranks Regression
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2-P Weibull Median Ranks Regression
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2-P Weibull Median Ranks Regression
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TTF Location Parameter, g
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TTF Location Parameter, g
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3-P Weibull Failure Math Model - TTF
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3-P Weibull Failure Math Model
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Failure Math Model pdf – f(t)
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Risk Threshold & Hazard Function
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Risk Threshold Logic
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Part Alternatives Hazard Functions & Risk Threshold
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Parts Alternatives Risk-based Scheduled Maintenance Interval, SMI
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Exponential v Weibull Failure Math Models
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Exponential v Weibull Hazard Function w/Risk Threshold
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Time-to-Repair Data
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Time-to-Repair Histogram
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3-P Weibull Failure Math Model
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Repair Math Model
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LDT Math Model - Baseline
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pre-Repair LDT Math Model
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Baseline
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post-Repair LDT Math Model
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Baseline
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pre-Repair LDT Math Model
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post-Repair LDT Math Model
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Deterministic Reliability, Maintainability & Availability
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Reliability Simulation Inputs
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Baseline Maintenance Labor Inputs
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PM Maintenance Labor Inputs
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Maintenance Costs Inputs
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Part Life-Cycle Simulation Factors
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Baseline Reliability Simulation Report
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Simulation Report for Part 1 Baseline
Results from 259 runs of sim time 40000-hrs
Part 1 Minimum Mean Maximum St.Dev 95% CL SEM 95% CL
Availability 0.98984 0.99051 0.99137 0.00030 0.99002 0.00002 0.99048
MTBF 628.51 683.68 734.35 19.74 651.09 1.23 681.65
MDT 6.32 6.54 6.80 0.08 6.68 0.005 6.55
MMT 1.67 1.76 1.88 0.03 1.81 0.002 1.76
LDT 4.79 4.86 4.79
System Failures 54 58.00 63 1.66 0.10 58.17
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PM Reliability Simulation Report
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Simulation Report for Part 1 - PM
Results from 259 runs of sim time 40000-hrs
Part 1 Minimum Mean Maximum St.Dev 95% CL SEM 95% CL
Availability 0.99305 0.99328 0.99342 0.00006 0.99318 0.000004 0.99328
MTBF 467.32 467.43 467.49 0.03 467.38 0.00 467.42
MDT 3.10 3.16 3.27 0.03 3.73 0.00 3.16
MMT 0.75 1.71 2.38 0.04 1.78 0.00 1.71
LDT 0.83 1.40 2.19 1.95 1.45
System Failures 85 85 85
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Reliability Simulation Summary
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Labor, Materials, Overhead & Lost Opportunity Costs Table
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Engineering Economics Basics
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,
0
, ,
1 1
1
n
i t
t
t
i t i t t
NPV PV
iPV A
i i
1
1 1
n
eqv n
i iA NPV
i
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Economic Analysis Expensed Costs &
Lost Opportunity Costs
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Part Uniform Recurring Equivalent Cost
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DetMean Det95%CL BSimMean BSim95%CL PMSimMean PMSim95%CL
A(CICC+Event) -$335 -$490 -$332 -$348 -$425 -$432
A(CExp+LostOp) -$2,118 -$3,816 -$2,090 -$2,239 -$1,452 -$1,747
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Part Operational Availability
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Baseline RCM
Part AO 0.99051 0.99328
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Stress-Directed Maintenance, SDM
Consumed life characterized by applied stress profile
Measures failure mechanisms acting on part
Not well developed for use by practioner
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SDM - The Present – Static Loading
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sop sdesign g
f (s) 1
f e
s
s s
s
95%LCLStrength
h(x)
x
1
( )x
h x
g
r
xr
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SDM - The Future - Wearout
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Summary
RCM yields definition of scheduled maintenance interval for critical parts
RCM measures part consumed life constrined by a risk threshold
RCM metrics: • CBM – Condition indicator
• TDM – Time in service
• SDM – Stress load profile
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