The research aims to develop a framework for evaluating operator well-being during the execution of industrial tasks, exploiting innovative technologies such as body tracking systems, virtual/augmented reality, and machine learning models. The proposed method allows for the assessment of both physical and cognitive ergonomics by adopting a proactive and reactive approach. The framework was validated through applications in various industrial sectors (logistics, assembly, teleoperation, etc.), including contexts involving the use of collaborative robots. The results demonstrate the adaptability of the method in different settings, providing a comprehensive overview of the operator's working conditions.
Il lavoro di ricerca svolto mira alla formulazione di un framework per la valutazione del benessere dell'operatore durante l'esecuzione di task industriali, sfruttando l'utilizzo di tecnologie innovative come sistemi di body tracking, realtà virtuale/aumentata e modelli di machine learning. Il metodo proposto consente di valutare l'ergonomia fisica e cognitiva adottando un approccio sia proattivo che reattivo. Il framework è stato validato attraverso applicazioni in diversi settori industriali (logistica, assemblaggio, teleoperazione, ecc.), inclusi contesti che coinvolgono l'uso di robot collaborativi. I risultati ottenuti mostrano l'adattabilità del metodo in diversi contesti, offrendo una visione completa delle condizioni di lavoro dell'operatore.
Operators' Well-Being in Industry 5.0: Balancing Physical And Cognitive Demands
LANZONI, Daniel
2025
Abstract
The research aims to develop a framework for evaluating operator well-being during the execution of industrial tasks, exploiting innovative technologies such as body tracking systems, virtual/augmented reality, and machine learning models. The proposed method allows for the assessment of both physical and cognitive ergonomics by adopting a proactive and reactive approach. The framework was validated through applications in various industrial sectors (logistics, assembly, teleoperation, etc.), including contexts involving the use of collaborative robots. The results demonstrate the adaptability of the method in different settings, providing a comprehensive overview of the operator's working conditions.File | Dimensione | Formato | |
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TesiLanzoniFinal.pdf
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37_Lanzoni-Daniel.pdf
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232.52 kB | Adobe PDF |
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https://hdl.handle.net/20.500.14242/296433
URN:NBN:IT:UNIBG-296433