Preliminary findings show a multidimensional model impacts cognitive load and task execution in manufacturing, suggesting enhanced cognitive ergonomics.
Cognitive assistance systems aim to enhance cognitive ergonomics by supporting operators in decision-making and task execution, addressing the high demands imposed by modern manufacturing processes. Existing frameworks for characterising cognitive assistance systems are fragmented, lacking a systematic approach to define and evaluate their constituent features. To address this gap, a multidimensional conceptual model is proposed, encompassing five core dimensions: cognitive functions, autonomy, adaptivity, interaction modality, and portability. A case study is conducted to preliminarily verify the model’s applicability by analyzing how variations in these core dimensions influence cognitive load, number of failures, and cycle time. Overall, the study provides two main contributions: (i) a multidimensional conceptual model to bridge the gap in the characterisation of cognitive assistance systems, and (ii) some preliminary findings from a case study in the context of Human-Robot Collaboration (HRC).
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M. De Bartolomei (2025) studied this question.
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