Maintenance Decision Making using State Dependent Markov Analysis with Failure Couplings

Xinyang Liu, Pingfeng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The maintenance decision making considering various types of coupling effect within system components has been a focus in the field of operation and maintenance (O and M) due to its wide applications in engineering systems with potentially significant economic benefits. Various opportunities as the coupling effect can provide, it leads to the difficulty in system modeling and policy establishment when multiple types of dependence exist in the system. This paper presents a novel approach to reflect economic dependence and stochastic dependence in the Markov model so that an optimal maintenance policy can be selected through policy performance comparison. Failure rates of system components change according to the health states of related components and combined maintenance actions introduce O and M time and cost savings. A case study has been used to demonstrate the developed method and further illustrate the benefit of combined maintenance actions in different O and M scenarios considering failure couplings among system components.

Original languageEnglish (US)
Title of host publication2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728171029
DOIs
StatePublished - Aug 2020
Event2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020 - Vancouver, Canada
Duration: Aug 20 2020Aug 23 2020

Publication series

Name2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020

Conference

Conference2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
CountryCanada
CityVancouver
Period8/20/208/23/20

Keywords

  • Markov Model
  • coupling effect
  • failure rate
  • maintenance

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation

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