{"title":"Digital Twins for Real-time Data Analysis in Industrie 4.0: Pathways to Maturity","authors":"Philip Stahmann, A. Krüger, Bodo Rieger","doi":"10.5220/0010688700003062","DOIUrl":null,"url":null,"abstract":": Digital twins are virtual copies of production systems’ physical components. In Industrie 4.0, they represent a promising opportunity for analysing production data in real-time and contribute to improved production planning and control. However, development of digital twins is challenging for companies due to missing guidance. In this research paper, we identify four maturity levels for digital twins for real-time data analysis based on a structured literature review and a market analysis that resulted in a total of 82 analysed contributions. The results are evaluated through a qualitative interview with four experts from academia and practice. Manufacturing companies can use the maturity levels for self-assessment and as a guideline. Future research can use the maturity levels for integration into holistic maturity models.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Innovative Intelligent Industrial Production and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0010688700003062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
: Digital twins are virtual copies of production systems’ physical components. In Industrie 4.0, they represent a promising opportunity for analysing production data in real-time and contribute to improved production planning and control. However, development of digital twins is challenging for companies due to missing guidance. In this research paper, we identify four maturity levels for digital twins for real-time data analysis based on a structured literature review and a market analysis that resulted in a total of 82 analysed contributions. The results are evaluated through a qualitative interview with four experts from academia and practice. Manufacturing companies can use the maturity levels for self-assessment and as a guideline. Future research can use the maturity levels for integration into holistic maturity models.