The digital transformation of collaborative networked manufacturing enterprises requires the building and the applying digital models representing the set of resources and processes knowledge. Modelling such digital copy of the physical system to perform real-time validation and optimization is quite complex and thus needs a big amount of data and some modelling patterns representing the operational semantics of the modelled elements. Generally, the modelling action has a specific application type. For this reason, the core challenge of the digital transformation modelling is to create a modular “digital model”, namely a decomposable and re-composable model, towards different applications. The authors propose an approach based on the combination of data-driven and model-based approaches, to identify and formalize modelling patterns, that combine for developing a modular executable model of the studied system.
Data-Driven Pattern-Based Constructs Definition for the Digital Transformation Modelling of Collaborative Networked Manufacturing Enterprises / Semeraro, Concetta; Lezoche, Mario; Panetto, Hervé; Dassisti, Michele; Cafagna, Stefano (IFIP ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGY). - In: Collaborative Networks and Digital Transformation : 20th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2019, Turin, Italy, September 23–25, 2019. Proceedings / [a cura di] Luis M. Camarinha-Matos; Hamideh Afsarmanesh; Dario Antonelli. - STAMPA. - Cham, CH : Springer, 2019. - ISBN 978-3-030-28463-3. - pp. 507-515 [10.1007/978-3-030-28464-0_44]
Data-Driven Pattern-Based Constructs Definition for the Digital Transformation Modelling of Collaborative Networked Manufacturing Enterprises
Concetta Semeraro;Michele Dassisti;
2019-01-01
Abstract
The digital transformation of collaborative networked manufacturing enterprises requires the building and the applying digital models representing the set of resources and processes knowledge. Modelling such digital copy of the physical system to perform real-time validation and optimization is quite complex and thus needs a big amount of data and some modelling patterns representing the operational semantics of the modelled elements. Generally, the modelling action has a specific application type. For this reason, the core challenge of the digital transformation modelling is to create a modular “digital model”, namely a decomposable and re-composable model, towards different applications. The authors propose an approach based on the combination of data-driven and model-based approaches, to identify and formalize modelling patterns, that combine for developing a modular executable model of the studied system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
