Modelling fatigue in manual and robot-assisted work for operator 5.0

Allemang-Trivalle, A., Donjat, J., Bechu, G., Coppin, G., Chollet, M. , Klaproth, O. W., Mitschke, A., Schirrmann, A. and Cao, C. G.L. (2024) Modelling fatigue in manual and robot-assisted work for operator 5.0. IISE Transactions on Occupational Ergonomics and Human Factors, (doi: 10.1080/24725838.2024.2321460) (PMID:38441578) (Early Online Publication)

Abstract

Occupational Applications: Fatigue, and many other human performance factors, impact worker wellbeing, and thus production quality and efficiency. Adopting the Industry 5.0 perspective, we propose that integrating human performance models into wider industrial system models can improve modeling accuracy and lead to superior outcomes. Integrating our Worker Fatigue Model as part of their industrial system architect model allowed Airbus, a leading aircraft manufacturer, to more accurately predict system performance as a function of the workforce makeup, which could be a combination of human workers and robots, or a combination of highly experienced and less experienced workers. Our approach demonstrates the importance and value of including human performance models in trade studies for introducing robots on the shop floor, and can be used to include various aspects of human performance in industrial system models to address specific task requirements or different levels of automation. Technical Abstract: Rationale: The advent of Industry 5.0 places a heightened focus on enhancing worker wellbeing during the digital transformation of factories. System models that ignore human workers yield suboptimal results in product design and system improvement.Purpose: In the aircraft industry, worker workload is of primary concern as most tasks are performed manually, leading to general fatigue and musculoskeletal disorders. Robot assistance could improve quality, efficiency and relieve workers from fatigue. To demonstrate the feasibility and value of integrating human performance models in system design at Airbus, a Worker Fatigue Model was developed, focusing on the effects of (1) automation (manual vs semi-automated), and (2) workforce makeup (various ratios of high-skilled to low-skilled workers). Our ultimate goal was to inform the development of effective policies and strategies for human-technology integration in Industry 5.0.Methods: We developed the Worker Fatigue Model by adapting existing fatigue models for workers in industrial environments and by considering worker characteristics, tasks, and the presence or absence of robot-assistance. Two different scenarios were simulated (fully manual and semi-automated), with input variables such as worker skill, age, and motivation, and output variables including overall fatigue and error probabilities were evaluated. The Worker Fatigue Model was integrated into the Airbus system model to conduct trade studies based on workforce characteristics.Results: Our findings revealed that the composition of the workforce (i.e., various ratios of high-skilled to low-skilled workers), alongside specific manufacturing technologies, significantly reduced worker fatigue, especially with higher ratios of high-skilled workers, and improved overall industrial system performance.Conclusions: Although applying our Worker Fatigue Model effectively demonstrated the feasibility and value of integrating human factors into early industrial system design, it remains a work in progress. Future work will aim to accurately represent the workload of human workers, including operational costs, when implementing robot assistance.

• Item Type: Articles
• Additional Information: This work was performed under Airbus Contract SP2104350 DISM.
• Status: Early Online Publication
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Chollet, Dr Mathieu
• Authors: Allemang-Trivalle, A., Donjat, J., Bechu, G., Coppin, G., Chollet, M., Klaproth, O. W., Mitschke, A., Schirrmann, A., and Cao, C. G.L.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: IISE Transactions on Occupational Ergonomics and Human Factors
• Publisher: Taylor & Francis
• ISSN: 2472-5838
• ISSN (Online): 2472-5846
• Published Online: 05 March 2024
• Copyright Holders: Copyright © 2024 The Authors
• First Published: First published in IISE Transactions on Occupational Ergonomics and Human Factors 2024
• Publisher Policy: Reproduced under a Creative Commons License