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Human Digital Twins: opportunities and challenges in sustainable manufacturing

Gabriele Becchio

Human Digital Twins: opportunities and challenges in sustainable manufacturing.

Rel. Alessandro Simeone, Paolo Claudio Priarone. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2023

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Abstract:

One of the most recurring words characterizing 2020’s is sustainability, which has tried to be pursued in almost any field as a requirement, especially for human activities which deeply interfere with the environment; one above all, manufacturing. Lots of new technologies which emerged in the last decades contributed to power sustainability in the manufacturing scenario, for all the three pillars in which sustainability can be declined: social, economic and environmental sustainability. The purpose of this thesis work is to present the concept of Digital Twin (DT), with a deep focus on the so-called Human Digital Twin (HDT) paradigm, a virtual representation of a person which can capture physical, biological and emotional traits. The main objective of building an HDT is to monitor and predict certain characteristics of, in the manufacturing context, industrial operators; by predicting their behaviour and health status, it’s possible to improve working conditions as well as preventing injuries, thus taking care of operator’s well-being which is the core of the modern Industry 5.0. A preliminary literature review proved that the use of an HDT specifically developed for manufacturing sustainability is seldom studied; this has been considered as an opportunity for the industry which deserved to be explored further. This work is intended to provide a better understanding of the current HDT applications in Sustainable Manufacturing which can be crucial for industry sustainability, plus giving a glimpse into the future promising developments.

Relators: Alessandro Simeone, Paolo Claudio Priarone
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 124
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management)
Classe di laurea: New organization > Master science > LM-31 - MANAGEMENT ENGINEERING
Aziende collaboratrici: Politecnico di Torino
URI: http://webthesis.biblio.polito.it/id/eprint/29604
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