Enhancing Worker Well-Being: A Study on Assistive Assembly to Mitigate Work-Related Musculoskeletal Disorders and Modulate Cobot Assistive Behavior

Open Access
Article
Conference Proceedings
Authors: André CardosoAna ColimEstela BichoAna BragaDébora PereiraSergio MonteiroPaula CarneiroNélson CostaPedro Arezes

Abstract: Industry 5.0 emphasizes human-centric approaches in manufacturing, aiming to prioritize worker well-being and productivity. Assembly lines are crucial in manufacturing, demand understanding, and improvement to enhance production performance and worker safety. This study addresses the importance of Assistive Assembly in improving working conditions, particularly at preventing Work-Related Musculoskeletal Disorders (WMSD). In this context, integrating collaborative robots (cobots) is a promising solution to ease workers’ burdens. However, its deployment in the assembly line requires further research to achieve better results. This research employs a human-centric approach in a laboratory setting to further explore the dynamics of assistive assembly to modulate a cobot's assistive behaviour. A proof-of-concept where participants assemble windows’ frames under Non-Assistive (NA) and Assistive (A) conditions was conducted, with real-time guidance provided in the latter. Perceived physical effort, kinematic analysis of upper limb movements, and electromyographic (EMG) analysis of muscle activity were performed. Results indicate significant reductions in perceived physical effort under the A condition compared to NA. Kinematic and EMG analyses reveal joint angles and muscle activation improvements, suggesting reduced physical strain in A condition. The study highlights the potential of assistive technologies, particularly cobots, in enhancing ergonomics and reducing physical strain in assembly processes, laying the groundwork for future advancements in Human-Robot Collaboration in industrial assembly lines.

Keywords: Ergonomics, WMSD, Assistive assembly, Collaborative robotics

DOI: 10.54941/ahfe1005528

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