Jingjing Wang , Lingyun Luo , Guoqing Mu , Yingying Ma , Chao Ni
{"title":"Joint optimization of quality control and maintenance policy for a production system with quality-dependent failures","authors":"Jingjing Wang , Lingyun Luo , Guoqing Mu , Yingying Ma , Chao Ni","doi":"10.1016/j.eswa.2025.126800","DOIUrl":null,"url":null,"abstract":"<div><div>A machine is either subject to hard failure or soft failure, while quality-dependent failure is usually ignored in production systems. However, in practice, non-conforming products generally accelerate the degradation process of production systems. To fill these gaps, this paper formulated an integrated model of the optimal quality control policy and maintenance policies under the quality-dependent failures for production systems. Since the severe degradation of product machines directly impacts the non-conforming rate, effective preventive and opportunistic maintenance actions are necessary. Moreover, the production system can timely be corrected from an out-of-control state to a control state after adopting a minimal repair. An opportunity is created based on the buffer inventory level instead of the machine degradation level, which is different from previous research. The production machine can be opportunistically maintained at the point of maximum inventory. The renewal process is utilized to derive the integrated optimization model, and the collaboration relationship among production, quality control and maintenance management problems is taken into consideration. The system’s total cost rate is minimized by optimizing the preventive maintenance threshold and sampling control coefficients. Numerical examples are given to illustrate the priority of the proposed model and the optimal results are obtained by differential evaluation algorithm, which provides a more meaningful perspective for managers.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"272 ","pages":"Article 126800"},"PeriodicalIF":7.5000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417425004221","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
A machine is either subject to hard failure or soft failure, while quality-dependent failure is usually ignored in production systems. However, in practice, non-conforming products generally accelerate the degradation process of production systems. To fill these gaps, this paper formulated an integrated model of the optimal quality control policy and maintenance policies under the quality-dependent failures for production systems. Since the severe degradation of product machines directly impacts the non-conforming rate, effective preventive and opportunistic maintenance actions are necessary. Moreover, the production system can timely be corrected from an out-of-control state to a control state after adopting a minimal repair. An opportunity is created based on the buffer inventory level instead of the machine degradation level, which is different from previous research. The production machine can be opportunistically maintained at the point of maximum inventory. The renewal process is utilized to derive the integrated optimization model, and the collaboration relationship among production, quality control and maintenance management problems is taken into consideration. The system’s total cost rate is minimized by optimizing the preventive maintenance threshold and sampling control coefficients. Numerical examples are given to illustrate the priority of the proposed model and the optimal results are obtained by differential evaluation algorithm, which provides a more meaningful perspective for managers.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.