Resumen de Bayes Inference for General Repairable Systems
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.
