Joint optimization of condition-based maintenance and component reallocation for phased-mission balanced systems with flexible structure considering imperfect substitution
{"title":"Joint optimization of condition-based maintenance and component reallocation for phased-mission balanced systems with flexible structure considering imperfect substitution","authors":"Siqi Wang , Shuyun Li , Lipo Mo","doi":"10.1016/j.ress.2025.111399","DOIUrl":null,"url":null,"abstract":"<div><div>In many practical situations, many balanced systems need to operate in multiple phases. Such systems usually have a different system structure for each phase. The system is balanced when the maximum state difference between all working components is less than a predetermined value. Component degradation is described by a Markov process and the state can be checked periodically. We propose a joint policy of condition-based component reallocation and maintenance for this balanced system. Non-working components can be used to replace working components for operation. Components can be repaired to an arbitrarily better state. The operation process of the balanced system is described as a Markov decision process and the optimal joint policy is obtained by a finite stage backward recursive iterative algorithm. In addition, two contrasting policies are proposed to compare with the proposed policy. Based on flexible manufacturing systems, a numerical study shows that the proposed joint policy is significantly better than the other two policies.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"264 ","pages":"Article 111399"},"PeriodicalIF":9.4000,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reliability Engineering & System Safety","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0951832025006003","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
In many practical situations, many balanced systems need to operate in multiple phases. Such systems usually have a different system structure for each phase. The system is balanced when the maximum state difference between all working components is less than a predetermined value. Component degradation is described by a Markov process and the state can be checked periodically. We propose a joint policy of condition-based component reallocation and maintenance for this balanced system. Non-working components can be used to replace working components for operation. Components can be repaired to an arbitrarily better state. The operation process of the balanced system is described as a Markov decision process and the optimal joint policy is obtained by a finite stage backward recursive iterative algorithm. In addition, two contrasting policies are proposed to compare with the proposed policy. Based on flexible manufacturing systems, a numerical study shows that the proposed joint policy is significantly better than the other two policies.
期刊介绍:
Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.