D. Mourtzis, Nikolaos Milas, K. Vlachou, Ioannis Liaromatis
{"title":"Digital transformation of structural steel manufacturing enabled by IoT-based monitoring and knowledge reuse","authors":"D. Mourtzis, Nikolaos Milas, K. Vlachou, Ioannis Liaromatis","doi":"10.1109/CoDIT.2018.8394874","DOIUrl":null,"url":null,"abstract":"The ever-increasing demands for timely product deliveries in structural steel manufacturing, require the evolution of traditional production practices. This can be achieved through the Internet of Things, Cyber-physical Systems, and other emerging technologies. Nevertheless, changes in the workflow of the production, due to the use of modern technologies, can be disruptive and cause complications. Towards this evolution of the industry, this paper proposes a method for monitoring the production in structural steel manufacturing considering Internet of Things and analyzing the data aiming to calculate product assembly complexity and reuse data to retrieve similar past orders. The main architecture, the software design, as well as the Internet of Things based monitoring system is presented following the main requirements of the industrial case study.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CoDIT.2018.8394874","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
The ever-increasing demands for timely product deliveries in structural steel manufacturing, require the evolution of traditional production practices. This can be achieved through the Internet of Things, Cyber-physical Systems, and other emerging technologies. Nevertheless, changes in the workflow of the production, due to the use of modern technologies, can be disruptive and cause complications. Towards this evolution of the industry, this paper proposes a method for monitoring the production in structural steel manufacturing considering Internet of Things and analyzing the data aiming to calculate product assembly complexity and reuse data to retrieve similar past orders. The main architecture, the software design, as well as the Internet of Things based monitoring system is presented following the main requirements of the industrial case study.