Analytical Reliability Centered Maintenance

1
RCM Conference Chattanooga, TN October 2002

• AnalyticalReliability Centered Maintenance
• Airline Example

Jahan Alamzad 1250 Aviation Avenue Suite
200M San Jose, CA 95110 Tel [phone] Fax
408-280-5700 Email jahan_a_at_msn.com
CA Advisors
2
Objectives

• Present applying Reliability-centered Maintenance
  (RCM) to develop analytical decision-support
  tools
• Discuss analytical applications of RCM in the
  airline industry
• Provide a structure of developments

3
Overview

• RCM focuses on understanding reliability
  characteristics
• Reliability characteristics can be abstracted
  analytically, and be represented by indicators
• Decisions can then be based on such indicators,
  providing significant benefits

Operations Management
Enhanced Asset Management
RCM
DecisionSupport
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Decision-support tools

• Reliability indicators
• understand the inherent reliability of parts
• estimate failure rate
• evaluate aging features
• Forecasting
• predict maintenance events
• anticipate maintenance activities
• Planning
• determine maintenance workload and material
  requirements during a specific period of time
• strategic assessment of maintenance needs
• identify support resources
• Optimization
• right-size inventory requirements
• repairable parts
• expendable parts
• design optimal maintenance program

5
RCM airline industry

• Genesis of RCM
• pre-deregulation
• observing enhanced reliability of modern flight
  equipment
• better ways to capitalized on increased
  performance
• New philosophy
• condition monitoring vs. overhaul
• life-limited parts
• threshold-limited parts
• Regulatory control
• highly-regulated operations commercially
  deregulated
• must prove before modifying maintenance practices
• regulatory requirements and best practices

6
Federal Aviation Regulations (FARs)

• Must comply with FARs as a certificated air
  carrier
• Policing mechanism
• auditing
• code of honor
• Mostly concerned with MRO (maintenance-repair-over
  haul) tracking and record-keeping
• manufacturer information
• manufactured date
• time since manufactured (flying hours, cycles,
  days)
• time since overhaul/installation (flying hours,
  cycles, days)
• history tracking
• positive tracking
• compliance with maintenance program
• Maintenance activity record keeping
• Requires substantial information system
  infrastructure to comply properly

RCM separation of data-processing and
decision-support
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Significant benefits

• Ease of developing analytical decision-support
  tools
• Available data
• standard
• accessible
• Quality decisions
• identify performance criteria
• monitor performance
• evaluate practices
• next-generation flight equipment maintenance
• asset management
• Industry-wide analysis
• Living RCM

Performance
Unit Cost
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Example engine maintenance
Engine Reliability System
Engine Removal Forecast
Spare Engine Planning System
Engine Life Optimizer
9
Structured approach
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Pilot study October 2000
Probability of failure before t p
one-parameter approach
two-parameter approach
ln-ln scale
ln scale
Slope beta parameter
f(p)
f(p)
Slope failure rate
Characteristic Life
ln scale
t
t

• Analysis process
• identify Scheduled vs Unscheduled events
• determine inter-event time
• build probability distribution function (pdf)
• transform data points
• do regression analysis
• determine parameters

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Results (one breaker model)

• One-parameter
• Failure rate 0.00149
• R-Squared 95.9

• Two-parameter
• Beta 1.06067
• Characteristic life 703.30
• R-Squared 98.0

• Application
• Input
• next scheduled maintenance 400 days
• time since last maintenance 120 days
• Output
• probability of failure beforescheduled
  maintenance
• expected time until next failure (days)

one-parameter
two-parameter
0.4488
0.4360
301
306
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Implementation

• Living RCM allows developing decision-support
  tools that reduce the unit cost of production and
  delivery

Unit Cost
Overage
Shortage
Resource Level

• Needed resources can be scientifically justified
  and decisions can be analytically supported

• Requires industry-wide data standardization

• Significant and immediate benefits
• better planning
• best practices