J. Friederich, Sune Chung Jepsen, S. Lazarova-Molnar, T. Worm
{"title":"Requirements for Data-Driven Reliability Modeling and Simulation of Smart Manufacturing Systems","authors":"J. Friederich, Sune Chung Jepsen, S. Lazarova-Molnar, T. Worm","doi":"10.1109/WSC52266.2021.9715410","DOIUrl":null,"url":null,"abstract":"Planning and deploying reliable Smart Manufacturing Systems (SMSs) is of increasing interest to both scholars and practitioners. High system reliability goes hand in hand with reduced maintenance costs and enables optimized repairs and replacements. To leverage the full potential of SMSs and enable data-driven reliability assessment, data needs should be precisely defined. System integration is a key concept of the Industry 4.0 initiative and it can aid the extraction of the needed data. In this paper, we study the data requirements for a novel middleware for SMSs to enable and support data-driven reliability assessment. We present this middleware architecture and demonstrate its application through a case study, which is used to generate exemplary data that corresponds to the derived requirements. The data requirements and the middleware architecture can support researchers in developing novel data-driven reliability assessment methods, as well as assist practitioners in designing and deploying SMSs in companies.","PeriodicalId":369368,"journal":{"name":"2021 Winter Simulation Conference (WSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC52266.2021.9715410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Planning and deploying reliable Smart Manufacturing Systems (SMSs) is of increasing interest to both scholars and practitioners. High system reliability goes hand in hand with reduced maintenance costs and enables optimized repairs and replacements. To leverage the full potential of SMSs and enable data-driven reliability assessment, data needs should be precisely defined. System integration is a key concept of the Industry 4.0 initiative and it can aid the extraction of the needed data. In this paper, we study the data requirements for a novel middleware for SMSs to enable and support data-driven reliability assessment. We present this middleware architecture and demonstrate its application through a case study, which is used to generate exemplary data that corresponds to the derived requirements. The data requirements and the middleware architecture can support researchers in developing novel data-driven reliability assessment methods, as well as assist practitioners in designing and deploying SMSs in companies.