Antonio Giuseppe Varrella
ICT for in-situ monitoring of metal Additive Manufacturing.
Rel. Edoardo Patti, Davide Cannizzaro, Santa Di Cataldo, Massimo Poncino. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2020
Abstract
In the Industry 4.0 scenario, early fault detection has gained a relevant importance. In this new digital context, Internet of Things (IoT) and machine learning have become fundamental. By collecting data from industrial processes and by analysing those, it’s possible to statistically detect, forecast and prevent faults. In this way, it’s possible to have a more secure working place and a more efficient working process in terms of times and costs. This approach has been widely applied to all kinds of processes, with attention to automatic ones. For this reason, a lot of approaches have been studied to early detect faults in the metal Additive Manufacturing (AM) technique.
The latter was a breakthrough in the industrial sector since early years of the XXI century and its nowadays widely adopted
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