Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32564
Title: Predicting the Impact of Cognitive Load and Psychological Well-Being among Workers in Manufacturing Environments
Authors: Orikpete, OF
Okwu, MO
Khalid, S
Abubakar, N
Tartibu, L
Chukwu, K
Keywords: cognitive load;psychological well-being;occupational health;safety;smart manufacturing;Industry 4.0
Issue Date: 25-Feb-2025
Publisher: Elsevier
Citation: Orikpete, O.F. et al. (2025) 'Predicting the Impact of Cognitive Load and Psychological Well-Being among Workers in Manufacturing Environments', Procedia Computer Science, 253, pp. 2859 - 2868. doi: 10.1016/j.procs.2025.02.010.
Abstract: The integration of Industry 4.0 technologies in manufacturing environments has significantly advanced production capabilities but has also introduced complex challenges for occupational health and safety. While previous studies have extensively explored the physical and technical impacts of these technologies, the psychological aspects, particularly cognitive load and psychological well-being, remain underexplored. This gap is significant because psychological factors play a critical role in influencing human performance and safety in complex, high-tech work environments. This study aims to address this gap by quantitatively investigating how cognitive load and psychological well-being affect safety incidents in smart manufacturing environments. Through a survey of 100 employees at a manufacturing company in Lagos, Nigeria, the relationship between cognitive load, psychological well-being, and reported safety incidents was analyzed. The findings reveal significant associations: higher cognitive load correlates with increased safety incidents, while better psychological well-being correlates with fewer incidents. This research underscores the critical need for interventions that manage cognitive load and enhance psychological well-being to improve safety outcomes in technologically advanced manufacturing settings.
Description: Data availability: Data used in this study can be shared on request.
Conference paper presented at the 6th International Conference on Industry 4.0 and Smart Manufacturing, Prague, Czech Republic, 20-22 November, 2024.
URI: https://bura.brunel.ac.uk/handle/2438/32564
DOI: https://doi.org/10.1016/j.procs.2025.02.010
Other Identifiers: ORCiD: Nura Abubakar https://orcid.org/0000-0002-4216-3057
Appears in Collections:Dept of Computer Science Research Papers

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