{"title":"Enablers and Barriers to the Implementation of Digital Twins in the Process Industry: A Systematic Literature Review","authors":"Matteo Perno, L. Hvam, Anders Haug","doi":"10.1109/IEEM45057.2020.9309745","DOIUrl":null,"url":null,"abstract":"Since its first introduction in 2002, the interest in the concept of \"Digital Twins\" has grown exponentially among researchers and industry practitioners. An increasing number of Digital Twin implementations are made in many industries. Given the novelty of the concept, companies from any industry type face significant challenges when implementing Digital Twins. Furthermore, only little research has been conducted in the process industry, which may be explained by the high complexity of representing and modeling the physics behind the production processes in an accurate manner. This study aims at filling this gap by providing a clear categorization of the main barriers that process companies face when implementing Digital Twins of their assets, as well as the key enabling factors and technologies that can be leveraged to overcome such challenges. Furthermore, a model based on the findings from the literature study is proposed. The results indicate a dearth in the literature focused on the process industry, therefore, key learnings from other industry sectors are gathered, and suggestions for further research are proposed.","PeriodicalId":226426,"journal":{"name":"2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM45057.2020.9309745","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Since its first introduction in 2002, the interest in the concept of "Digital Twins" has grown exponentially among researchers and industry practitioners. An increasing number of Digital Twin implementations are made in many industries. Given the novelty of the concept, companies from any industry type face significant challenges when implementing Digital Twins. Furthermore, only little research has been conducted in the process industry, which may be explained by the high complexity of representing and modeling the physics behind the production processes in an accurate manner. This study aims at filling this gap by providing a clear categorization of the main barriers that process companies face when implementing Digital Twins of their assets, as well as the key enabling factors and technologies that can be leveraged to overcome such challenges. Furthermore, a model based on the findings from the literature study is proposed. The results indicate a dearth in the literature focused on the process industry, therefore, key learnings from other industry sectors are gathered, and suggestions for further research are proposed.