DIGITEM
Digital Twins for Technologies and Manufacturing
Digital Twins in manufacturing increase efficiency and reduce costs. DIGITEM explores Digital Twins in systems and processes within the Italian and European manufacturing industry to enhance efficiency, promote sustainability and innovation, focusing on modeling, control, and optimization.
KEYWORDS
Digital Twin
Manufacturing Systems
Industry 4.0/5.0
Manufacturing Execution System (MES)
Production Monitoring
Mission
DIGITEM Section aims at contributing, in synergy with the industrial environment, to the knowledge development on Digital Twins, by identifying the gaps between what is proposed at the research level and the current application of Digital Twins in the manufacturing sector. DIGITEM focuses on advanced Digital Twin models to enhance the performance of manufacturing systems and their production processes in terms of monitoring, control, supervision, and Manufacturing Execution System (MES).
The topics of interest of the Section are:
- Digital Twin of production processes:The use of Digital Twins to predict the properties of materials composing the component/product during processing, thus enabling production interventions to correct any deviations from the desired requirements and defining the relationship between product properties and the parameters governing the processes, ensuring a high quality standard.
- Digital Twin nei sistemi produttivi: The use of simulation tools provided by Digital Twins to support planning activities and performance evaluation in various demand or critical scenarios, also aiming to simultaneously optimize the technical and environmental performance of the system by identifying production plans that reduce energy consumption and promote the implementation of circular economy strategies.
DIGITEM aims to create shared knowledge on Digital Twins to improve the entire manufacturing sector through a network of stakeholders connected to the automotive, aerospace, and semiconductor industries. Within this network, the Section aims to address the main current challenges for the implementation of DTs, improving the performance of systems and processes by combining expertise and technologies developed in academic and industrial environments.
- Advanced Digital Twin models to enhance the performance of production systems and processes
- Create shared knowledge to improve the manufacturing sector
Coordinatori e componenti fondatori
Sarvpriya Raj Kumar
Coordinatore industriale
Dassault Systèmes
Erica Pastore, Politecnico di Torino
Andrea Matta, Politecnico di Milano
Nicla Frigerio, Politecnico di Milano
Antonio Costa, Università di Catania
Sergio Fichera, Università di Catania
Arianna Alfieri, Politecnico di Torino
Giacomo Maculotti, Politecnico di Torino
Giuseppe Casalino, Politecnico di Bari
Livan Fratini, Università degli Studi di Palermo
Giuseppe Ingarao, Università degli Studi di Palermo
Antonello Astarita, Università degli Studi di Napoli Federico II
Enrico Savio, Università di Padova
Giovanni Lucchetta, Università di Padova
Giovanni, Lugaresi, KU Leuven
Sarvpriya Raj Kumar, Dassault Systèmes,
Giuseppe Cirrone, NTET Group SpA,
Daniela Fontana, COMAU S.p.A.
Ivan Mondino, Avio Aero
Simone Marchesi, Anton Paar Italia