MAINTENANCE OF COMPLEX SYSTEMS: ISSUES AND CHALLENGES

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MAINTENANCE OF COMPLEX SYSTEMS ISSUES AND
CHALLENGES

• Professor D.N.P. Murthy
• The University of Queensland
• Brisbane, Australia

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OUTLINE

• Concepts and Overview
• Evolution of Maintenance
• Study of Maintenance
• Illustrative case Rail Operations
• Outsourcing and Leasing
• Modelling and Analysis
• Issues and Challenges

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CONCEPTS AND OVERVIEW
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RELIABILITY

• Reliability of a product (system) conveys the
  concept of dependability, successful operation or
  performance and the absence of failures.
  Unreliability (or lack of reliability) conveys
  the opposite.

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SYSTEMS

• All systems are unreliable in the sense that they
  degrade with age and/or usage and ultimately
  fail.
• A system is said to have failed when it is
  incapable of meeting the designed performance.

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MAINTENANCE

• Preventive Maintenance Actions to control the
  degradation and reduce the likelihood of a
  failure.
• Corrective Maintenance Actions to restore a
  failed unit back to operational state.
• If systems do not degrade and/or fail there is no
  need for maintenance.

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STUDY OF MAINTENANCE

• A proper study of maintenance requires a good
  understanding of reliability theory.
• There are several aspects to both reliability and
  maintenance and they cover a wide spectrum as
  indicated in the next few slides.

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RELIABILITY THEORY

• Deals with the interdisciplinary use of
  probability, statistics and stochastic modelling,
  combined with engineering insights into the
  design and the scientific understanding of the
  failure mechanisms, to study the various aspects
  of reliability.

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RELIABILITY THEORY

• Encompasses several topics
• Reliability modelling
• Reliability analysis and optimisation
• Reliability engineering
• Reliability science
• Reliability technology
• Reliability management
• Etc.

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ASPECTS OF MAINTENANCE

• Technical
• Engineering (Reliability, Maintainability)
• Science (Predicting degradation)
• Technologies (Sensor, IT, etc)
• Etc.
• Management
• Operational (Execution of maintenance tasks)
• Tactical (Planning of maintenance tasks)
• Strategic (Linking to business objectives)
• Etc.

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EVOLUTION OF MAINTENANCE
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MAINTENANCE (Pre 1940)

• Only corrective maintenance (CM) and no planned
  preventive maintenance (PM)

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MAINTENANCE (Post 1950)

• Use of planned PM actions
• Optimal PM policies based on models involving
  product reliability (a design decision)

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MAINTENANCE (Post 1970)

• RCM, TPM concepts looking an impact on failure
  on business performance
• Condition based maintenance

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MAINTENANCE (Post 1990)

• Maintenance and usage (production) level
  decisions made jointly

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STUDY OF MAINTENANCE
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SOME OBSERVATIONS

• Reliability depends on design and manufacturing
• Degradation and failures depend on usage
  (production) rate
• Failures impact on performance
• Cost implications
• Linking of technical and commercial aspects

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OVERALL FRAMEWORK
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STAKEHOLDERS

• Several stakeholders
• Owner of asset
• Operators (users)
• External agents (maintenance service)
• Regulators (Health and safety)
• Etc.
• The interests and objective of each is different.

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EQUIPMENT MAINTENANCE
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INFRASTUCTURE MAINTENANCE
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SCIENTIFIC APPROACH

• Identifying the key elements and the interaction
  between the elements
• Use of models Qualitative and Quantitative
• This involves model building and this in turn
  requires proper data collection and analysis.

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MICRO vs. MACRO

• The number of elements involved depends on the
  focus of the study
• Micro Few elements Technical and narrow
• The rate of degradation as a function of usage
• Scheduling of maintenance tasks
• Macro Many elements Management and broad
• Deciding on maintenance strategy many technical
  and commercial elements

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AN ILLUSTRATIVE CASE

• RAIL OPERATIONS

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CHANGES IN OPERATIONS

• Past Government owned, operated and maintained
  the complete system (infrastructure and rolling
  stock)
• Current Infrastructure owned by an independent
  business unit of government
• Rolling stock Owned and operated by several
  independent business units

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KEY ELEMENTS
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DECISION - MAKING

• Increase in traffic (goods and passenger)
• How to cope? Several options -- More frequent
  operations More wagons Greater axle load
  Faster speeds etc
• Implications More load on the track - faster
  degradation
• What should be the optimal strategy?

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DECISION - MAKING

• Need to integrate operation (commercial decision)
  with maintenance (technical decision)
• Increase load? Short term gain but long term
  loss!
• Upgrade track? Costly
• Design better rolling stock?

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CHALLENGES

• Need to model the different elements (technical,
  commercial, operational and managerial)
• Need to understand the underlying degradation
  processes involved (Reliability science)
• Adequate data to build and validate models
  (Reliability modeling)

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OTHER ISSUES

• Rolling stock Operators
• Owing versus leasing
• Outsourcing of maintenance
• Joint optimization of maintenance and operations
• Maintenance In-house versus outsourcing
• Contracts between different parties

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MODELLING

• Damage and degradation resulting from the
  interaction between rolling stock and
  infrastructure
• Modeling track failures distributed models with
  two dimensional ROCOF
• ?(t,x), t time and x spatial coordinate
• Modeling contracts
• Dispute resolution

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MAINTENANCE OUTSOURCING

• D-1 What (components) need to be maintained?
• D-2 When should the maintenance be carried out?
• D-3 How should the maintenance be carried out

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MAINTENANCE OUTSOURCING

• Two parties
• Owner of equipment
• Service agent
• Different scenarios

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LEASING

• Operating Lease Lessor provides the maintenance
• Finance Lease Lessee has to provide maintenance
• Sale and Buyback Lease Mainly with
  infrastructure assets

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KEY ELEMENTS
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THREE SCENARIOS
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FRAMEWORK
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MODELING AND ANALYSIS
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METHODOLOGY

• Characterization of the relevant elements
  (depends on the problem)
• Selection of appropriate model formulations
• Estimation of model parameters (need appropriate
  data)
• Model validation
• Model analysis and optimization

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SYSTEM CHARACTERIZATION

• The number of elements needed depends on the
  problem
• Level of understanding Low to high
• Sources for getting the information
• Level of detail determines complexity
• Trade-off between complexity and tractability
  (data needed, analysis, etc.)

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MODEL FORMULATION

• Two approaches to modeling
• Black-box Based solely on data (empirical
  approach)
• White box Based on the physical characterization
  of the underlying processes
• Stochastic formulations As variables change with
  time in an uncertain manner

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APPROACH

• Game-theoretic if there are multiple
  decision-makers
• Different scenarios
• Leader follower Stackelberg game
• No leader Nash game
• Data and information available to each
  decision-maker becomes important

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STACKELBERG GAME

• Leader
• Owner (e.g., rail infrastructure)
• Service agent (e.g. maintenance of lifts)

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ISSUES AND CHALLENGES
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ISSUES

• Stackelberg game is closely related to agency
  theory Principal and Agent Principal
  delegating tasks to Agent
• Auction Rail operators bidding for number of
  trips per day
• Tendering for carrying out maintenance
• Contract critical element

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ISSUES IN AGENCT THEORY
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DATA RELATED ISSUES

• Data collection
• Data classification
• Structured and unstructured data
• Equipment, cost, servicing, etc.
• Data storage
• Data problems (delays, missing, uncertainties,
  errors, etc.)
• Information content

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DATA ANALYSIS

• Preliminary data analysis To get better insight
• More refined analysis Various plots to assist in
  model selection
• Data for estimating model parameters (various
  methods)

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CHALLENGES

• Maintenance of complex system involves dealing
  with several issues
• Bulk of the literature on maintenance deals with
  different elements treated separately and from a
  micro perspective
• Some literature dealing from a macro perspective

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CHALLENGES

• Lot of scope to do new research in maintenance of
  complex systems
• Models will be more complex
• Need concepts from many disciplines Operations
  research (game theory) Economics (agency
  theory), Reliability theory Stochastic
  processes IT, Statistics, etc.

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REFERENCES

• Blischke, R. and Murthy, D.N.P. (2000),
  Reliability, Wiley, New York
• Jiang, R. and Murthy, D.N.P. (2008), Maintenance
  Decision Models for Management, Science Press,
  Beijing
• Kobbacy, K.A.H. and Murthy, D.N.P. (eds) (2008),
  Complex System Maintenance Handbook, Springer
  Verlag, London
• Murthy, D.N.P, Atrens, A and Eccleston, J.A.
  (2002), Strategic maintenance management, Journal
  of Quality in Maintenance Engineering, 8, 287-305

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REFERENCES

• Murthy, D.N.P. Ashgarizadeh, E. (1999), Optimal
  decision making in a maintenance service
  operation, European Journal of Operational
  Research, 116, 259- 273
• Jaturnnatee, J., Murthy, D.N.P. and
  Boodiskulchok, R. (2005), Optimal preventive
  maintenance of leased equipment, European Journal
  of Operational Research, 174, 201-215
• Blischke, W.R., Karim, M.Z. and Murthy, D.N.P.
  (2010), Warranty Data Collection and Analysis,
  Under preparation for publication.