No abstract

Nowadays companies have to face the rapid evolution of their competitive environment. In the field of design, project managers are aware of both the impact of the designers' competencies on the project performance and of the requirement for a fast development of these competencies. However, they have difficulties in updating competency reference banks and then, in correctly matching the available competencies and missions that have to be performed. This issue of competence management mainly concerns competency allocation and project team building. In research literature, numerous research works suffer from poor competence modelling. Even if some authors have linked competence with work situation, there is often a lack of documentation concerning knowledge capturing about a designer's work situation which would help managers characterise competency. In this paper, we present the architecture of a novel approach based on the traceability of design activities which aims at assisting competency characterisation through qualitative features of the work situation in which this competency is activated. #

No abstract

This paper addresses the problems of data management and analytics for decision-aid by proposing a new vision of Digital Shadow (DS) which would be considered as the core component of a future Digital Twin. Knowledge generated by experts and artificial intelligence, is transformed into formal business rules and integrated into the DS to enable the characterization of the real behavior of the physical system throughout its operation stage. This behavior model is continuously enriched by direct or derived learning, in order to improve the digital twin. The proposed DS relies on data analytics (based on unsupervised learning) and on a knowledge inference engine. It enables the incidents to be detected and it is also able to decipher its operational context. An example of this application in the aeronautic machining industry is provided to stress both the feasibility of the proposition and its potential impact on shop floor performance.