Cognitive Load Assessment in Maintenance Operations: A Systematic Review in the Context of Industry 5.0

Industry 5.0 emphasizes human-centered manufacturing through a systematic integration of enabling technologies, including Augmented Reality (AR) and Artificial Intelligence (AI). While Industry 4.0 technologies enhance operational efficiency, they also introduce significant cognitive demands on human operators, particularly in maintenance tasks, requiring robust frameworks for mental workload assessment and workplace ergonomics optimization. This study presents a systematic literature review (SLR), updated to May 2025, which allowed to classify cognitive workload assessment methods into three main approaches: subjective, physiological, and behavioural approaches, highlighting the predominant use of one method for each category (NASA-TLX questionnaires, EEG-based monitoring, and eye-tracking techniques respectively). Furthermore, the study examines digital technologies used to support cognitive workload management, such as Virtual Reality (VR) training systems, haptic feedback devices, and Decision Support Systems (DSS). Key findings reveal research gaps in real-time task allocation based on cognitive workload, dynamic decision-making frameworks, and human factors integration in DSS architectures. This review highlights the need for a developing comprehensive, real-time DSS solution that combine physiological and psychological metrics to enhance operator well-being and production efficiency within Industry 4.0 environments.