Reliability-based optimization of imperfect preventive maintenance with Bayesian estimation

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL Quality Engineering Pub Date : 2022-12-05 DOI:10.1080/08982112.2022.2150085
Selma Gürler, D. Göksülük, Deniz Türsel Eliiyi
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引用次数: 1

Abstract

Abstract In this study, we present a sequential imperfect preventive maintenance model for a component subject to degradation. We use an age reduction reliability model for scheduling preventive maintenance, which is performed whenever the component’s reliability falls below the reliability threshold level, R. The problem is considered under lack of data, in which the Bayesian methodology is more appropriate than the frequentist view for estimating the unknown parameters of the model. We assume a fixed duration for preventive maintenance, whereas the duration of corrective maintenance is an exponential random variable. We model the total expected cost over all cycles and find the optimal preventive maintenance plan until a replacement based on the reliability threshold value. We also conducted a numerical study for sensitivity analysis of the developed model.
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基于贝叶斯估计的不完全预防性维修可靠性优化
摘要在本研究中,我们提出了一个针对退化部件的连续不完全预防性维护模型。我们使用减龄可靠性模型来安排预防性维护,每当部件的可靠性低于可靠性阈值水平R时,就会执行该模型。该问题是在缺乏数据的情况下考虑的,其中贝叶斯方法比频率论观点更适合估计模型的未知参数。我们假设预防性维护的持续时间是固定的,而纠正性维护的时间是指数随机变量。我们对所有周期的总预期成本进行建模,并根据可靠性阈值找到最佳预防性维护计划,直到更换为止。我们还对所开发的模型进行了灵敏度分析的数值研究。
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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来源期刊
Quality Engineering
Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
10.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.
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