A sequential inspection and replacement policy for degradation-based systems

Zhicheng Zhu, Yisha Xiang, Suzan Alaswad, C. R. Cassady
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引用次数: 4

Abstract

Condition-based maintenance (CBM) has been extensively studied. However, the majority of existing CBM research either consider a periodic inspection schedule or a fixed preventive maintenance threshold. While policies with periodic inspections and/or fixed maintenance threshold are easy to implement in practice, they may incur more-than-necessary inspections and induce more failures. In this paper, we develop a sequential CBM policy for systems subject to stochastic degradation. The aim of the proposed policy is to prevent or delay failures and perform maintenance activities just in time. Unlike conventional preventive maintenance that often fixes the inspection interval and the preventive maintenance threshold, both the next inspection time and the corresponding maintenance threshold in this paper are dynamically determined based on the current state of the system. The proposed sequential predictive maintenance policy is particularly important and applicable for general non-homogeneous degradation processes. The proposed model enables optimal scheduling of inspection and preventive maintenance decisions, in order to minimize the long-run maintenance cost rate including inspection, preventive and corrective maintenance costs. The performance of the proposed predictive maintenance policy is evaluated using a simulation-based optimization approach. Frequency of system failures and total maintenance cost rates are computed and compared with a bench mark maintenance policy, a periodic inspection/replacement policy. Our results show that there can be potential savings from the proposed predictive maintenance policy.
基于退化的系统的顺序检查和更换策略
基于状态的维修(CBM)得到了广泛的研究。然而,现有的大多数CBM研究要么考虑定期检查计划,要么考虑固定的预防性维护阈值。虽然具有定期检查和/或固定维护阈值的策略在实践中很容易实现,但它们可能导致不必要的检查并导致更多的故障。在本文中,我们开发了一个随机退化系统的顺序CBM策略。建议策略的目的是防止或延迟故障,并及时执行维护活动。与常规预防性维护通常固定检查间隔和预防性维护阈值不同,本文的下一次检查时间和相应的维护阈值都是根据系统的当前状态动态确定的。提出的顺序预测性维护策略对于一般的非均质退化过程尤为重要和适用。该模型实现了检查和预防性维护决策的最优调度,以最小化包括检查,预防性和纠正性维护成本在内的长期维护成本率。使用基于仿真的优化方法对所提出的预测性维护策略的性能进行了评估。计算系统故障频率和总维护成本率,并与基准维护策略、定期检查/更换策略进行比较。我们的研究结果表明,提出的预测性维护策略可以节省潜在的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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