Bayesian failure-rate modeling and preventive maintenance optimization

Dmitriy Belyi, Elmira Popova, David P. Morton, Paul Damien*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

New results are derived for the optimal preventive maintenance schedule of a single item over a finite horizon, based on Bayesian models of a failure rate function. Two types of failure rate functions—increasing and bathtub shapes—are considered. For both cases, optimality conditions and efficient algorithms to find an optimal maintenance schedule are given. A Bayesian parametric model for bathtub-shaped failure rate functions is used, while the class of increasing failure rate functions are tackled by an extended gamma process. We illustrate both approaches using real failure time data from the South Texas Project Nuclear Operating Company in Bay City, Texas.

Original languageEnglish (US)
Pages (from-to)1085-1093
Number of pages9
JournalEuropean Journal of Operational Research
Volume262
Issue number3
DOIs
StatePublished - Nov 1 2017

Keywords

  • Bayesian nonparametrics
  • Maintenance optimization
  • Markov chain Monte Carlo
  • Stochastic optimization

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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