Digital Twins (DT) are very useful tools in the industrial field because they allow to simulate and predict the behavior of a real object or production chain, allowing the reduction of production losses, the optimization of processes, the identification of any anomalies.

To create a DT heterogeneous skills are needed: infrastructural to create the data collection architecture from IoT sensors, IT to manage data and process them, mathematics to model the real process with the data in possession and create control/forecast algorithms and HPC since the amount of data collected is such that it is necessary to manage the algorithms that process them in a scalable way.

Prerequisites:

Basic knowledge of IT/OT processes

Basic knowledge of using IA/HPC technologies

Teachers:

Andrea Bartolini (University of Bologna)

Francesco Beneventi (University of Bologna)

Andrea Borghesi (University of Bologna)

Luigi Capone (Leonardo Labs)

Mirko Cestari (CINECA)

Francesco Meoni (BI-REX)

Ivan Spisso (Leonardo Labs)