Investigating the impact of cognitive assistive technologies on human performance and well-being: an experimental study in assembly and picking tasks

Current industrial scenarios are characterised by increasingly demanding activities, especially order picking and assembly tasks. These activities require high levels of adaptability and manual dexterity, requirements that workers can fulfil, thus underscoring their paramount role. However, these tasks are becoming more complex and subjecting workers to greater cognitive strain. In this context, Industry 4.0 (I4.0) technologies that provide cognitive support (cognitive assistive technologies) are essential for reducing cognitive load, facilitating decision-making, improving performance and safeguarding workers’ well-being. This study investigates the effectiveness of cognitive assistive technologies through laboratory experiments with 37 participants performing assembly and order picking tasks. Performance and well-being outcomes are evaluated based on task completion time and perceived workload. Results suggest that among the technologies investigated, pick-by-light is the most effective in assisting users, easing decision-making, and ensuring performance and well-being. This study contributes to explorative works that focus on the human-centric outcomes of assistive technologies, examining their effectiveness in providing cognitive support. Practical and managerial insights are derived to help engineers and managers choose cognitive assistive technologies that effectively support workers and enhance their performance and well-being.

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Publication Details

Journal
International Journal of Production Research
Published
2024-08-26
DOI
https://doi.org/10.1080/00207543.2024.2394090
Citations
13
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
8.37

Funders

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article

Investigating the impact of cognitive assistive technologies on human performance and well-being: an experimental study in assembly and picking tasks

Sotirios Panagou, Fabio Sgarbossa, Andrea Lucchese
13 citations
International Journal of Production Research
Human-Automation Interaction and Safety
8.37
article

Investigating the impact of cognitive assistive technologies on human performance and well-being: an experimental study in assembly and picking tasks

Sotirios Panagou, Fabio Sgarbossa, Andrea Lucchese
article en
13 citations

Abstract

Current industrial scenarios are characterised by increasingly demanding activities, especially order picking and assembly tasks. These activities require high levels of adaptability and manual dexterity, requirements that workers can fulfil, thus underscoring their paramount role. However, these tasks are becoming more complex and subjecting workers to greater cognitive strain. In this context, Industry 4.0 (I4.0) technologies that provide cognitive support (cognitive assistive technologies) are essential for reducing cognitive load, facilitating decision-making, improving performance and safeguarding workers’ well-being. This study investigates the effectiveness of cognitive assistive technologies through laboratory experiments with 37 participants performing assembly and order picking tasks. Performance and well-being outcomes are evaluated based on task completion time and perceived workload. Results suggest that among the technologies investigated, pick-by-light is the most effective in assisting users, easing decision-making, and ensuring performance and well-being. This study contributes to explorative works that focus on the human-centric outcomes of assistive technologies, examining their effectiveness in providing cognitive support. Practical and managerial insights are derived to help engineers and managers choose cognitive assistive technologies that effectively support workers and enhance their performance and well-being.

International Journal of Production ResearchVol. 63(6)
Norwegian University of Science and Technology (NO), Polytechnic University of Bari (IT)
European Commission
Reduced inequalities
Openalex Percentile: Top 2%
Human-Automation Interaction and Safety
8.37
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