Bayes inference for general repairable systems

Rong Pan, Steven E. Rigdon

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Models for repairable systems are often characterized by the assumed effect of a failure and the subsequent repair. As-bad-as-old models lead to the nonhomogeneous Poisson process and as-good-as-new models lead to the renewal process. We study Bayesian methods for some models that are a compromise between the bad-as-old and the good-as-new models. For the case of multiple systems, we consider a hierarchical Bayes model. We use Markov chain Monto Carlo methods to approximate properties of the posterior distributions.

Original languageEnglish (US)
Pages (from-to)82-94
Number of pages13
JournalJournal of Quality Technology
Issue number1
StatePublished - Jan 2009


  • Hierarchical bayes model
  • Imperfect repair
  • Markov chain Monte Carlo
  • Power law process

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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