Using Cognitive Work Analysis to deploy collaborative digital twins : application to predictive maintenance
Résumé
The digital twin is a technology that expands the possibilities of manufacturers thanks to its various applications, particularly for the application of predictive maintenance. In the context of Industry 4.0, technical agents such as digital twins tend towards more autonomy. Indeed, one of its characteristics lies in its partial or total capacity to act on its physical counterpart. Therefore, it is necessary to consider the digital twin and the human agent as cooperating agents. Under this perspective, decision loops between the digital twin and human agent is necessary in the deployment of the digital twin. The JUPITER project aims to develop the digital twin for predictive maintenance of the SCAP platform, a manufacturing line. The objective of this paper is to show how Cognitive Work Analysis (CWA) could contribute to the definition of the allocation of the decision making activity between the digital twin and the human. Two CWA analysis were applied: the Work Domain Analysis (WDA) and the Social Organization and Cooperation Analysis with his tool Contextual Template Activity (SOCA-CAT). The functions identified by the WDA highlighted the allocation decision between the cooperative agents and the SOCA-CAT provided a contextualization of this allocation. The allocation of the decision making activity was considered in terms of the level of automation between the digital twin and the human agent.
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