. Musculoskeletal disorders (MSDs) represent a prevalent global occupational health concern, primarily associated with high biomechanical solicitations, mental workload and work pace. Although cobots have shown promise in reducing risks of MSDs, a question of interest still persists as to how the pace in hybrid human-machine collaboration will affect the operator, in terms of both physical and cognitive health and the production.. This study aimed to analyse the impact of pace on productivity, operators' posture and mental workload in a human-cobot collaboration. The study, involving 20 participants engaged in a collaborative task with a cobot under three cobot-led paces, assessed productivity rapid upper limb assessment (RULA) scores (posture), dual task performance (cognitive resources) and NASA task load index (NASA-TLX) scores (workload).. The findings revealed that an excessively high pace had counterproductive effects, leading to reduced efficiency and increased susceptibility to MSDs, both in terms of physical and mental workloads.. In the context of a human-cobot collaboration, it is imperative to adapt the pace to operators' abilities in order to ensure optimal productivity while preserving their health, emphasizing the need for a balanced approach to pace management in such collaborative work scenarios.
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http://dx.doi.org/10.1080/10803548.2024.2440265 | DOI Listing |
Int J Occup Saf Ergon
January 2025
UR 3450 DevAH, Université de Lorraine, France.
. Musculoskeletal disorders (MSDs) represent a prevalent global occupational health concern, primarily associated with high biomechanical solicitations, mental workload and work pace. Although cobots have shown promise in reducing risks of MSDs, a question of interest still persists as to how the pace in hybrid human-machine collaboration will affect the operator, in terms of both physical and cognitive health and the production.
View Article and Find Full Text PDFAppl Ergon
September 2024
Laboratoire D'Informatique de Grenoble, Université Grenoble Alpes, CS 40700, 38058 Cedex, Grenoble, France.
The 5.0 industry promotes collaborative robots (cobots). This research studies the impacts of cobot collaboration using an experimental setup.
View Article and Find Full Text PDFFront Robot AI
December 2023
Department of General Psychology, University of Padova, Padova, Italy.
As a result of Industry 5.0's technological advancements, collaborative robots (cobots) have emerged as pivotal enablers for refining manufacturing processes while re-focusing on humans. However, the successful integration of these cutting-edge tools hinges on a better understanding of human factors when interacting with such new technologies, eventually fostering workers' trust and acceptance and promoting low-fatigue work.
View Article and Find Full Text PDFInt J Environ Res Public Health
March 2023
Institute of Psychology, Faculty of Social Sciences, University of Silesia in Katowice, 40-007 Katowice, Poland.
Modern factories are subject to rapid technological changes, including the advancement of robotics. A key manufacturing solution in the fourth industrial revolution is the introduction of collaborative robots (cobots), which cooperate directly with human operators while executing shared tasks. Although collaborative robotics has tangible benefits, cobots pose several challenges to human-robot interaction.
View Article and Find Full Text PDFSci Rep
November 2022
Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, 010000, Astana, Kazakhstan.
This study investigates how different motion planning algorithms, implemented on a collaborative robot (cobot), are perceived by 48 human subjects. The four implemented algorithms ensure human safety based on the concept of speed and separation monitoring, but differ based on the following characteristics: (a) the cobot motion happens either along a fixed path or with a trajectory that is continuously planned in real time via nonlinear model predictive control, to increase cobot productivity; (b) the cobot speed is further reduced-or not-in real time based on heart rate measurements, to increase perceived safety. We conclude that (1) using a fixed path-compared to real-time motion planning-may reduce productivity and, at least when heart rate measurements are not used to modify the cobot speed, increases perceived safety; (2) reducing cobot speed based on heart rate measurements reduces productivity but does not improve perceived safety; (3) perceived safety is positively affected by habituation during the experiment, and unaffected by previous experience.
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