Determining operators’ cognitive workload and individual effects using wearable sensing technologies in the Industry 4.0 context

The digital transformation of Industry 4.0 has demonstrated a growing emphasis on the concepts of "human in the loop" and "Operator 4.0." These concepts aim not only to enhance the efficiency of human and system collaboration but also to prioritise the well-being of human operators, ensuring they work in a healthy and sustainable manner. As the digital transformation brings the opportunity to utilise the technologies extensively throughout the work, more personal sensation and perception, attention and working memory can be occupied on humans and thus can be considered as significant work stressors that affect the cognitive workload of humans.

Cause and effect of cognitive workload are complex, cognitive workload can be influenced by multiple factors with task complexity and other social-psychological perspectives, considering these personal perspectives could provide deeper insights into cognitive workload variations. However, defining and monitoring cognitive workload requires more objective and short-interval measures and the elimination of the intervention techniques presented in this thesis, especially when operators are performing their tasks during work. In addition, highly reliable analysis methods are required and presented in this thesis to ensure that dynamic over several seconds and cumulative cognitive workloads within segments of interest can be captured and analysed.

The cognitive workload variations have been modelled in this thesis through linear mixed models and thus using data-driven approach, proved that expect for complexity, expertise level, conscientiousness and emotionality are also effects of cognitive workload variations. This contribution is useful for the manufacturing and operators that the precise monitoring of cognitive workload variations could not only provide a foundation to support industrial ergonomists to design a better optimal cognitive workload workspace and ensure the operators mental wellbeing is under the healthy conditions.