Pattern-based Digital Twin for Optimizing Manufacturing Systems: A Real Industrial-Case Application. Issue 1 (2021)

• Record Type: Journal Article
• Authors: Semeraro, Concetta; Lezoche, Mario; Panetto, Hervé; Dassisti, Michele
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 1(2021)
• Page Start: 307
• Page End: 312
• Publication Date: 2021
• Subjects: Digital Twin -- CPS -- Data-driven -- Modelling Patterns -- Predictive Manufacturing; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.08.157
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The 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.