文章基本信息

标题：Pattern-based Digital Twin for Optimizing Manufacturing Systems: A Real Industrial-Case Application
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作者：Concetta Semeraro ; Mario Lezoche ; Hervé Panetto 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：1
页码：307-312
DOI：10.1016/j.ifacol.2021.08.157
语种：English
出版社：Elsevier
摘要：AbstractThe digital twin has received strong interests from researchers and industries since it allows predictive manufacturing by integrating the cyber and the physical space. An important prerequisite for the cyber–physical integration is a proper and highly-accurate digital model. Considering the complexity of digital modelling, the paper aims at developing and using predefined modelling patterns to enable building digital models independently of the specific application domain. The idea is explored and validated on a real case study by designing a set of patterns to create a digital twin model prototype adopted to control and optimize the manufacturing system taken into account.
关键词：KeywordsDigital TwinCPSData-drivenModelling PatternsPredictive Manufacturing