Abstract
Human-centred approaches in industrial facilities emphasize the importance of considering the workers as the main stakeholders in the production process. Mainly, it is for ensuring their well-being in an inclusive and sustainable work environment. From the occupational health and safety perspective, one of the main challenges is the musculoskeletal risks caused by a variety of industrial tasks. Therefore, an online monitoring mechanism that assesses proactively the posture is needed to adjust the production tasks and environment towards the workers’ well-being. This paper introduces a model of a digital twin capable of representing the posture of a human worker and assesses simultaneously the risk to the musculoskeletal system. The digital twin identifies the landmarks of a human body through a pose recognition solution and assesses in an enhanced REBA method the risk of the worker from a musculoskeletal perspective.
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Jimenez, JF., Maire, JL. (2024). ErgoTwin: A Digital Twin Model for Monitoring the Postural Risks on Industrial Workers. In: Borangiu, T., Trentesaux, D., Leitão, P., Berrah, L., Jimenez, JF. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2023. Studies in Computational Intelligence, vol 1136. Springer, Cham. https://doi.org/10.1007/978-3-031-53445-4_21
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DOI: https://doi.org/10.1007/978-3-031-53445-4_21
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