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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part O. Journal of Risk and Reliability >Selective maintenance optimisation considering random common cause failures and imperfect maintenance
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Selective maintenance optimisation considering random common cause failures and imperfect maintenance

机译:考虑随机常见原因故障和不完美维护的选择性维护优化

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摘要

This article addresses a selective maintenance optimisation problem for systems subject to random common cause failures. A system is likely to suffer from several random common cause failures during a given mission. Random common cause events, which occur with a specific probability distribution, may result in the simultaneous failures of multiple elements. Because time is one of the most crucial maintenance resources, a time-based imperfect maintenance model is proposed to quantify the maintenance efficiency of each candidate maintenance action. To meet the demands of the next mission, a selective maintenance model is proposed to optimally identify a subset of maintenance activities to be performed on certain elements of a system. A genetic algorithm and Monte Carlo simulation method is presented to solve the proposed selective maintenance optimisation problem. Illustrative examples combined with detailed discussions are presented to demonstrate the effectiveness of the proposed model. The results show that the proposal of time-based imperfect maintenance model can yield better maintenance results, while ignoring random common cause failures in selective maintenance optimisation may produce biased maintenance decisions and system reliability.
机译:本文为随机常见原因故障受到的系统,解决了一个选择性维护优化问题。在给定的任务期间,系统可能遭受几种随机常见的原因失败。用特定概率分布发生的随机通用原因事件可能导致多个元素的同时失败。由于时间是最重要的维护资源之一,提出了一种基于时间的不完美维护模型来量化每个候选维护动作的维护效率。为了满足下一个任务的要求,提出了一种选择性维护模型,以最佳地识别要在系统的某些元素上执行的维护活动的子集。提出了一种遗传算法和蒙特卡罗模拟方法来解决所提出的选择性维护优化问题。提出了与详细讨论结合的说明性实施例以证明所提出的模型的有效性。结果表明,基于时间的不完美维护模型的提议可以产生更好的维护结果,同时忽略随机常见的原因在选择性维护优化中的故障可能产生偏置的维护决策和系统可靠性。

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