Zhaoxiang Chen, Yihai He, Yixiao Zhao, Xiao Han, Zheng He
{"title":"Selective Maintenance Decision for Multistate Manufacturing System Based on Extended State Task Network","authors":"Zhaoxiang Chen, Yihai He, Yixiao Zhao, Xiao Han, Zheng He","doi":"10.1109/IEEM.2018.8607692","DOIUrl":null,"url":null,"abstract":"In actual production, the best maintenance operations of multistate manufacturing system cannot be implemented at intervals due to the limitation of maintenance costs. In this case, selective maintenance decisions are widely adopted. However, previous selective maintenance decisions only consider the basic reliability, which cannot fully describe the operating characteristics of multistate manufacturing system. Therefore, this paper proposes a selective maintenance decision with the goal of maximizing the mission reliability for multistate manufacturing system. Firstly, the new connotation of selective maintenance is defined to characterize the ability of a multistate manufacturing system to meet the variable task demand state. Secondly, the Extended State Task Network is proposed to characterize the operating characteristics of manufacturing system and the mission reliability model. Thirdly, under the condition of fixed maintenance cost, a selective maintenance decision method based on Particle Swarm Optimization algorithm is derived, which makes the mission reliability of next operation to be maximized. Finally, in order to verify the effectiveness of the proposed method, a case study of selective maintenance decision for a multistate cylinder head manufacturing system is given.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2018.8607692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In actual production, the best maintenance operations of multistate manufacturing system cannot be implemented at intervals due to the limitation of maintenance costs. In this case, selective maintenance decisions are widely adopted. However, previous selective maintenance decisions only consider the basic reliability, which cannot fully describe the operating characteristics of multistate manufacturing system. Therefore, this paper proposes a selective maintenance decision with the goal of maximizing the mission reliability for multistate manufacturing system. Firstly, the new connotation of selective maintenance is defined to characterize the ability of a multistate manufacturing system to meet the variable task demand state. Secondly, the Extended State Task Network is proposed to characterize the operating characteristics of manufacturing system and the mission reliability model. Thirdly, under the condition of fixed maintenance cost, a selective maintenance decision method based on Particle Swarm Optimization algorithm is derived, which makes the mission reliability of next operation to be maximized. Finally, in order to verify the effectiveness of the proposed method, a case study of selective maintenance decision for a multistate cylinder head manufacturing system is given.