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A Bayesian Approach to Maintenance Policy Based on Cost and Downtime After Non-Renewing Warranty

机译:基于成本和非更新保修期后停机时间的贝叶斯维修策略

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摘要

This article adopts a Bayesian approach to derive an optimal maintenance policy following the expiration of non renewing warranty. If the system fails during its warranty period, it is replaced with a new one. If the system failure occurs after the warranty period is expired, then it is minimally repaired at each failure. As the criteria to determine the optimal replacement period, we use the expected cost and the expected downtime during the life cycle of the system. Under the replacement model considered, we first derive the formulas to compute the expected downtime per unit time and the expected cost rate per unit time in general. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach, under which such unknown parameters are updated using the observed data. The overall value function suggested by Jiang and Ji (2002) is utilized to combine the expected downtime and the expected cost rate and to determine the optimal maintenance period. Numerical examples are presented for illustrative purpose.
机译:本文采用贝叶斯方法,以在非更新保修期满后得出最佳维护策略。如果系统在保修期内出现故障,则将其更换为新的系统。如果在保修期到期后发生系统故障,则每次出现故障时都应进行最少的维修。作为确定最佳更换期限的标准,我们使用系统生命周期内的预期成本和预期停机时间。在考虑的替换模型下,我们首先导出公式,以计算通常的单位时间预期停机时间和单位时间预期成本率。当假定失效时间服从参数未知的Weibull分布时,我们提出了一种基于贝叶斯方法的最优维护策略,在该策略下,使用观察到的数据更新了这些未知参数。 Jiang和Ji(2002)提出的总价值函数用于组合预期的停机时间和预期的成本率,并确定最佳的维护周期。给出数值示例用于说明性目的。

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