Although manufacturing work environments have become increasingly automated, the principles derived from Industry 5.0 emphasize the creation of human-centered workplaces, where the resilience and social sustainability of the workforce are top organizational priorities. It emphasizes human well-being, collaboration between humans and machines, and the balanced management of physical and cognitive demands. This shift is particularly relevant in assembly environments, where, despite technological advancements, many tasks are still performed manually or with technological assistance, placing significant physical and cognitive demands on workers. While physical ergonomics has largely investigated the minimization of workload to jointly optimize system efficiency and workforce well-being, cognitive factors-such as decision-making, learning, and process monitoring-are increasingly acknowledged as critical elements of worker performance, particularly in collaborative and manual assembly systems. Understanding how these physical and cognitive demands interact has become essential for designing inclusive and sustainable work environments aligned with Industry 5.0 principles. In this work, we review the contributions of the last five years that have evaluated and detected cognitive workload and stress in assembly systems, aiming to identify which technologies and settings have been considered so far. By synthesizing existing research, this review provides valuable insights into cognitive ergonomics in assembly, resulting in a better understanding of current approaches and informing future research toward the development of more efficient, adaptive, and inclusive worker-centered systems.

Cognitive Ergonomics Assessment in Manual and Collaborative Assembly Systems

Caprari G.
;
Katiraee N.;Berti N.;Battini D.
2025

Abstract

Although manufacturing work environments have become increasingly automated, the principles derived from Industry 5.0 emphasize the creation of human-centered workplaces, where the resilience and social sustainability of the workforce are top organizational priorities. It emphasizes human well-being, collaboration between humans and machines, and the balanced management of physical and cognitive demands. This shift is particularly relevant in assembly environments, where, despite technological advancements, many tasks are still performed manually or with technological assistance, placing significant physical and cognitive demands on workers. While physical ergonomics has largely investigated the minimization of workload to jointly optimize system efficiency and workforce well-being, cognitive factors-such as decision-making, learning, and process monitoring-are increasingly acknowledged as critical elements of worker performance, particularly in collaborative and manual assembly systems. Understanding how these physical and cognitive demands interact has become essential for designing inclusive and sustainable work environments aligned with Industry 5.0 principles. In this work, we review the contributions of the last five years that have evaluated and detected cognitive workload and stress in assembly systems, aiming to identify which technologies and settings have been considered so far. By synthesizing existing research, this review provides valuable insights into cognitive ergonomics in assembly, resulting in a better understanding of current approaches and informing future research toward the development of more efficient, adaptive, and inclusive worker-centered systems.
2025
Proceedings of the Summer School Francesco Turco
XXX AIDI Summer School "Francesco Turco"
   Made in Italy Circolare e Sostenibile
   MICS
   Next-Generation EU
   Italian PNRR –M4 C2, Invest 1.3 –D.D. 1551.11-10-2022, PE00000004
   C93C22005280001

   Model and Methods for an Active Ageing Workforce: An International Academy
   MAIA
   European Union’s Horizon 2020 research and innovation programme
   Marie Sklodowska- Curie grant agreement No 873077
   MAIA-2020-MSCA-RISE 2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3574139
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