M. Khakifirooz, Dimitri Cayard, C. Chien, M. Fathi
{"title":"A System Dynamic Model for Implementation of Industry 4.0","authors":"M. Khakifirooz, Dimitri Cayard, C. Chien, M. Fathi","doi":"10.1109/ICSSE.2018.8520101","DOIUrl":null,"url":null,"abstract":"With advances in information and telecommunication technologies and data-enabled decision making, smart manufacturing can be an essential component of sustainable development. In this era, the promising relevant opportunities to reduce costs to boost productivity and improve quality is based on the integration or combination of simulated replicas of actual equipment, Cyber-Physical Systems (CPS) and regionalized or decentralized decision making into a smart factory. However, this integration also presents the industry with different unique challenges. The stream of the data from sensors, robots, and CPS can aid to make the manufacturing smart. Therefore, it would be an increased need for modeling, optimization, and simulation to the value delivery of manufacturing data. This paper aims to outline the approach that was used to develop a system dynamics model to evaluate a superior design of “Industry 4.0” implementation for smart manufacturing.","PeriodicalId":431387,"journal":{"name":"2018 International Conference on System Science and Engineering (ICSSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2018.8520101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
With advances in information and telecommunication technologies and data-enabled decision making, smart manufacturing can be an essential component of sustainable development. In this era, the promising relevant opportunities to reduce costs to boost productivity and improve quality is based on the integration or combination of simulated replicas of actual equipment, Cyber-Physical Systems (CPS) and regionalized or decentralized decision making into a smart factory. However, this integration also presents the industry with different unique challenges. The stream of the data from sensors, robots, and CPS can aid to make the manufacturing smart. Therefore, it would be an increased need for modeling, optimization, and simulation to the value delivery of manufacturing data. This paper aims to outline the approach that was used to develop a system dynamics model to evaluate a superior design of “Industry 4.0” implementation for smart manufacturing.