Dorota Lang, P. Wunderlich, Mario Heinz, Lukasz Wisniewski, J. Jasperneite, O. Niggemann, C. Röcker
{"title":"Assistance system to support troubleshooting of complex industrial systems","authors":"Dorota Lang, P. Wunderlich, Mario Heinz, Lukasz Wisniewski, J. Jasperneite, O. Niggemann, C. Röcker","doi":"10.1109/WFCS.2018.8402380","DOIUrl":null,"url":null,"abstract":"In ever changing world, the industrial systems become more and more complex. Machine feedback in the form of alarms and notifications, due to its growing volume, becomes overwhelming for the operator. In addition, expectations in relation to system availability are growing as well. Therefore, there exists strong need for new solutions guaranteeing fast troubleshooting of problems that arise during system operation. The approach proposed in this study uses advantages of the Asset Administration Shell, machine learning, and human-machine interaction in order to create the assistance system which holistically addresses the issue of troubleshooting complex industrial systems.","PeriodicalId":350991,"journal":{"name":"2018 14th IEEE International Workshop on Factory Communication Systems (WFCS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th IEEE International Workshop on Factory Communication Systems (WFCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WFCS.2018.8402380","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
In ever changing world, the industrial systems become more and more complex. Machine feedback in the form of alarms and notifications, due to its growing volume, becomes overwhelming for the operator. In addition, expectations in relation to system availability are growing as well. Therefore, there exists strong need for new solutions guaranteeing fast troubleshooting of problems that arise during system operation. The approach proposed in this study uses advantages of the Asset Administration Shell, machine learning, and human-machine interaction in order to create the assistance system which holistically addresses the issue of troubleshooting complex industrial systems.