Prédiction de la complexité d'un produit usiné : proposition d'un modèle basé sur l'analyse du modèle 3D enrichi

Abstract

These days, product manufacturing through material removing remains one of the most widely used techniques to manufacture high-precision and complex products. Research has shown that complex products which are incorrectly managed will be detrimental to company performance during the manufacturing process. Therefore, a valid and accurate quantitative metric to identify high-complexity products early on in the manufacturing process is most valuable to a company in a design-for-manufacturing context. In the present work, we propose a complexity metric model based solely on the information found in a Model-Based Definition (MBD) Computer-Aided Design (CAD) file. The proposed metric is a multiplicative model based on three factors: the volume to be machined, the order of magnitude of the geometrical elements and the ponderation value of the annotations. Our investigation is based on the analysis of 54 different parts picked from our industrial partner’s technical document database. The results of our work demonstrate that our model is highly correlated to a part’s evaluated complexity. Furthermore, empirical validation of our complexity metric model has shown that it could predict the complexity value of a part Under 15% of discrepancy between the predicted value and its target value. Alternatively, to increase its accuracy and reliability, we recommended to pursue further research in several directions such as features geometric context or to test our model in others industries. Nonetheless, with its current quality, our model could help engineering teams identify highcomplexity products as early as the design phase.

Date	21 Jun 2016
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Roland Maranzana (Supervisor) & Antoine Tahan (Co-supervisor)