Knowledge capitalization in mechatronic collaborative design

Mouna Fradi (1, 2) , Raoudha Gaha (3, 2) , Faïda Mhenni (1, 4) , Abdelfattah Mlika (2) , Jean-Yves Choley (1, 4)

1 QUARTZ - Laboratoire QUARTZ
2 ENISo - Ecole Nationale d'Ingénieurs de Sousse
3 Roberval - Roberval
4 ISAE-Supméca - ISAE-Supméca Institut Supérieur de Mécanique de Paris

In mechatronic collaborative design, there is a synergic integration of several expert domains, where heterogeneous knowledge needs to be shared. To address this challenge, ontology-based approaches are proposed as a solution to overtake this heterogeneity. However, dynamic exchange between design teams is overlooked. Consequently, parametric-based approaches are developed to use constraints and parameters consistently during collaborative design. The most valuable knowledge that needs to be capitalized, which we call crucial knowledge, is identified with informal solutions. Thus, a formal identification and extraction is required. In this paper, we propose a new methodology to formalize the interconnection between stakeholders and facilitate the extraction and capitalization of crucial knowledge during the collaboration, based on the mathematical theory ‘Category Theory’ (CT). Firstly, we present an overview of most used methods for crucial knowledge identification in the context of collaborative design as well as a brief review of CT basic concepts. Secondly, we propose a methodology to formally extract crucial knowledge based on some fundamental concepts of category theory. Finally, a case study is considered to validate the proposed methodology.

Domaines: Sciences de l'ingénieur [physics]

Mouna Fradi, Raoudha Gaha, Faïda Mhenni, Abdelfattah Mlika, Jean-Yves Choley. Knowledge capitalization in mechatronic collaborative design. Concurrent Engineering: Research and Applications, 2021, 30 (1), pp.32-45. ⟨10.1177/1063293X211050438⟩. ⟨hal-03792939⟩