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Bayesian Approach for Adaptive Sequential Preventive Maintenance Policy

机译:自适应序贯预防性维修政策的贝叶斯方法

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This paper proposes an adaptive sequential preventive maintenance(PM) policy under which each PM not only reduces the hazard rate, but also slows down the degradation process of the system. We derive mathematical formulas to evaluate the expected cost rate per unit time by incorporating the PM cost, repair cost and replacement cost and propose the optimal sequential PM policy. Assuming that the failure times follow Weibull distribution, we adopt a Bayesian approach to update unknown parameters and determine the optimal sequential PM policy. The effect of some parameters on the optimal PM policy is measured numerically by sensitivity analysis and some numerical examples are presented for illustrative purposes.
机译:本文提出了一种自适应序贯预防性维护策略,该策略不仅降低了风险率,而且减缓了系统的退化过程。我们得出数学公式,通过结合PM成本,维修成本和更换成本来评估每单位时间的预期成本率,并提出最佳的顺序PM策略。假设故障时间遵循威布尔分布,我们采用贝叶斯方法更新未知参数并确定最佳顺序PM策略。通过敏感性分析,对某些参数对最佳PM策略的影响进行了数值测量,并出于说明目的给出了一些数值示例。

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