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Bayes Inference for General Repairable Systems

Summary: [This abstract is based on the authors' abstract.] Models for repairable systems can be characterized by the effect of the failure and the subsequent repair. Conventional repair models consider two extremes: As-bad-as-old models that lead to the nonhomogeneous Poisson process and the as-good-as-new models that lead to the renewed process. Bayesian methods are considered for models that are a compromise between these extremes. For multiple systems, a hierarchical Bayesian model is proposed. Markov chain Monte Carlo methods are use to approximate properties of the posterior distributions.

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  • Topics: Process Management
  • Keywords: Bayesian methods, Hierarchical systems, Repairable systems, Markov chains, Monte Carlo methods, Power law process
  • Author: Pan, Rong; Rigdon, Steven E.
  • Journal: Journal of Quality Technology