A core aspect of Industry 4.0 (I4.0) is the continuous communication between humans, machines and products enabled by cyber-physical production systems. The high complexity of tasks to be processed require an increasing cognitive effort. Under this perspective, the maintenance procedures are changing. Maintenances activities in I4.0 context can be considered as complex decision-making processes where the best option to solve problems is strongly affected by the capacity of the operator to quickly process the given information. The purpose of the paper consists to evaluate the complexity of cognitive-oriented tasks that must be performed by operators in planned maintenance procedures. At this scope, the joint adoption of the TACOM measure and the graph theory is pursued. The proposed methodology is tested on different planned maintenance procedures related to automotive and mechanical production sectors. The results showed a strong correlation between graph structures in terms of both the number of events and links, and the cognitive demand required for the information processing.

Evaluation of the Complexity of Cognitive-Oriented Tasks in Planned Maintenance Procedures

Lucchese, Andrea
;
Marino, Antonella;Mossa, Giorgio;Mummolo, Giovanni
2022

Abstract

A core aspect of Industry 4.0 (I4.0) is the continuous communication between humans, machines and products enabled by cyber-physical production systems. The high complexity of tasks to be processed require an increasing cognitive effort. Under this perspective, the maintenance procedures are changing. Maintenances activities in I4.0 context can be considered as complex decision-making processes where the best option to solve problems is strongly affected by the capacity of the operator to quickly process the given information. The purpose of the paper consists to evaluate the complexity of cognitive-oriented tasks that must be performed by operators in planned maintenance procedures. At this scope, the joint adoption of the TACOM measure and the graph theory is pursued. The proposed methodology is tested on different planned maintenance procedures related to automotive and mechanical production sectors. The results showed a strong correlation between graph structures in terms of both the number of events and links, and the cognitive demand required for the information processing.
International Conference on Industrial Systems
978-3-030-97946-1
978-3-030-97947-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/244521
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