Integrating human-centric simulations in educational production linesadvancing ergonomics for industry 5.0 applications

  1. Ruiz de la Torre, Aitor 1
  2. Borregan, Jon 1
  3. Pikatza, Naiara 1
  4. Rio, Rosa Maria 1
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Journal:
International Journal of Production Management and Engineering (IJPME)

ISSN: 2340-4876,  2340-5317

Year of publication: 2024

Volume: 12

Issue: 2

Pages: 141-157

Type: Article

DOI: 10.4995/IJPME.2024.20919 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: International Journal of Production Management and Engineering (IJPME)

Abstract

This research in the Industry 5.0 field focuses on a human-centered simulation of the FAS200 SMC educational production line, utilizing Tecnomatix Process Simulate Human software for developing a virtual human environment. A key aspect of this study is the integration of inertial sensors, enhancing the accuracy and depth of ergonomic analysis. These sensors play a pivotal role in capturing precise human movement data, crucial for ergonomic assessments. Adopting a defined working methodology, the study extensively employs the RULA method to evaluate operator postures in the production line. This approach has led to significant ergonomic improvements, evidenced by a 40 percent reduction in the RULA index at each workstation. The integration of inertial sensors has been instrumental in achieving these results, providing detailed insights into human movements and interactions with the production environment. The research transcends traditional ergonomic assessments by incorporating a new human-centered approach, emphasizing the well-being of individuals working alongside machines. This approach, bolstered by the use of inertial sensors, marks a significant advancement in ergonomic studies, aligning with the principles of Industry 5.0. The findings hold substantial potential for application in industrial settings, signaling a shift towards more human-friendly and efficient industrial practices.

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