Giorgio Giacalone
Digital Twin and Machine Learning solutions for the Manufacturing Environment.
Rel. Andrea Sanna. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2021
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Abstract
The advent of Industry 4.0 has brought manufacturing realities to become more flexible and prone to reconfiguration in order to adapt to unexpected events and clients needs. Smart Manufacturing wants to encourage the usage of innovative technologies to promote the digital transformation, especially exploiting the possibilities offered by cyber physical systems and virtual environments (VEs). Digital Twins (DTs) have been widely adopted to virtually reproduce the physical world and to integrate real environments with their digital counterpart. The development of a DT solution for a production line can be used for monitoring activities, to assess limitations and costs of the real counterpart and to simulate enhancements before implementing possible solutions in the real world.
Also, the big amount of data that flow between from the physical assets to their virtual replica can be used to train machine learning systems
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