Xiaotong Wei , Yalong Wang , Yingdong He , Zixian Liu , Zhen He
{"title":"Integrated production, maintenance and quality control for complex manufacturing systems considering imperfect maintenance and dynamic inspection","authors":"Xiaotong Wei , Yalong Wang , Yingdong He , Zixian Liu , Zhen He","doi":"10.1016/j.ress.2025.110896","DOIUrl":null,"url":null,"abstract":"<div><div>In complex manufacturing systems, production equipment typically consists of numerous components. Such equipment is prone to high failure rates in the early stages of use owing to a combination of manufacturing defects, design defects, and improper initial setup. In formulating production, maintenance, and quality policies, most joint optimization models consider that equipment failure rates gradually increase with use time. However, they ignore failures that might occur in the early stages of equipment use, resulting in high quality costs. Considering manufacturing defects in the early use of complex manufacturing systems, this study formulates a new joint optimization model that aims to determine the safety stock level, production cycle length, preventive maintenance threshold, and inspection sampling ratio that minimize the expected unit cost of the system. First, we consider the equipment failure rate with a bathtub curve shape and develop a corresponding dynamic sampling strategy. Second, we divide the production process into six scenarios and develop a condition-based maintenance policy based on the degree of equipment deterioration, production time, and average output quality limits. We solve the model using Monte Carlo simulation and design of experiments. Sensitivity analysis and comparative study verify that the proposed strategy can flexibly adapt to production changes with fewer inspections and lower costs.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"259 ","pages":"Article 110896"},"PeriodicalIF":9.4000,"publicationDate":"2025-02-15","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/S0951832025000997","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 complex manufacturing systems, production equipment typically consists of numerous components. Such equipment is prone to high failure rates in the early stages of use owing to a combination of manufacturing defects, design defects, and improper initial setup. In formulating production, maintenance, and quality policies, most joint optimization models consider that equipment failure rates gradually increase with use time. However, they ignore failures that might occur in the early stages of equipment use, resulting in high quality costs. Considering manufacturing defects in the early use of complex manufacturing systems, this study formulates a new joint optimization model that aims to determine the safety stock level, production cycle length, preventive maintenance threshold, and inspection sampling ratio that minimize the expected unit cost of the system. First, we consider the equipment failure rate with a bathtub curve shape and develop a corresponding dynamic sampling strategy. Second, we divide the production process into six scenarios and develop a condition-based maintenance policy based on the degree of equipment deterioration, production time, and average output quality limits. We solve the model using Monte Carlo simulation and design of experiments. Sensitivity analysis and comparative study verify that the proposed strategy can flexibly adapt to production changes with fewer inspections and lower costs.
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.