Pattern-based digital twin for optimizing manufacturing systems: A real industrial-case application

Concetta Semeraro (1) , Mario Lezoche (1) , Hervé Panetto (1) , Michele Dassisti (2)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 Polytechnic University of Bari / Politecnico di Bari

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.

Mots clés: Digital Twin; CPS; Data-driven; Modelling Patterns; Predictive Manufacturing

Domaines: Ingénierie assistée par ordinateur

Concetta Semeraro, Mario Lezoche, Hervé Panetto, Michele Dassisti. Pattern-based digital twin for optimizing manufacturing systems: A real industrial-case application. 17th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2021, Jun 2021, Budapest (virtual), Hungary. pp.307-312, ⟨10.1016/j.ifacol.2021.08.157⟩. ⟨hal-03253774⟩