Toward human-centric Industry 5.0: a framework for cognitive workload assessment in maintenance and assembly

In the transition from Industry 4.0 to Industry 5.0 (I5.0), the focus of manufacturing is shifting toward human-centric, sustainable, and resilient systems. A key challenge in this evolution is managing the cognitive workload (CWL) of operators, especially during complex tasks such as maintenance and assembly. These activities are central to industrial operations and often involve high mental demands due to task variability, decision-making under pressure, and human–machine collaboration. Despite a growing body of research on CWL, there remains a lack of clarity regarding the most suitable assessment methods for specific industrial tasks. This study addresses that gap by conducting a systematic literature review to identify how CWL is measured across distinct categories of maintenance and assembly operations, the results of which were used to develop a framework for measuring CWL and a matrix of CWL assessment guidelines. Findings show that different task categories present distinct cognitive demands, which influence the selection of CWL assessment methods. Routine and structured tasks are typically assessed using subjective or basic physiological measures, while more complex and dynamic tasks increasingly require multimodal approaches combining subjective, physiological, and performance-based data. Additionally, the review revealed intra-domain similarities and inter-domain differences that highlight the need for task-specific CWL evaluation strategies. Based on these insights, the study proposes a framework that maps suitable CWL assessment methods to categories of maintenance and assembly tasks, along with a CWL assessment guidelines matrix to support method selection according to task complexity and operational impact. By offering a structured approach to CWL evaluation, this work contributes to the transition toward adaptive, human-centric industrial systems in line with the I5.0 paradigm.