On the use of Machine Learning to Defeature CAD Models for Simulation
Article dans une revue avec comité de lecture
Date
2013Journal
Computer-Aided Design and ApplicationsRésumé
Numerical simulations play more and more important role in product development cycles and are increasingly complex, realistic and varied. CAD models must be adapted to each simulation case to ensure the quality and reliability of the results. The defeaturing is one of the key steps for preparing digital model to a simulation. It requires a great skill and a deep expertise to foresee which features have to be preserved and which features can be simplified. This expertise is often not well developed and strongly depends of the simulation context. In this paper, we propose an approach that uses machine learning techniques to identify rules driving the defeaturing step. The expertise knowledge is supposed to be embedded in a set of configurations that form the basis to develop the processes and find the rules. For this, we propose a method to define the appropriate data models used as inputs and outputs of the learning techniques.
Fichier(s) constituant cette publication
Cette publication figure dans le(s) laboratoire(s) suivant(s)
Documents liés
Visualiser des documents liés par titre, auteur, créateur et sujet.
-
Communication avec acteThis paper adresses the way machine learning techniques based on neural networks can be used to predict the impact of simplification processes on CAD model for heat transfer FEA purposes.
-
Communication avec acteEssential when adapting CAD model for finite element analysis, the defeaturing ensures the feasibility of the simulation and reduces the computation time. Processes for CAD model preparation and defeaturing tools exist but ...
-
Communication avec acteBeing able to estimate a priori the impact of DMU preparation scenarios for a dedicated activity would help identifying the best scenario from the beginning. Machine learning techniques are a means to a priori evaluate a ...
-
Article dans une revue avec comité de lectureControlling the well-known triptych costs, quality and time during the different phases of the Product Development Process (PDP) is an everlasting challenge for the industry. Among the numerous issues that are to be ...
-
Communication avec acteLEBERT, Déborah;
PLOUZEAU, Jeremy; FARRUGIA, Jean-Philippe;
DANGLADE, Florence;
MERIENNE, Frédéric (Springer Nature Switzerland, 2022-08-28)
Ensuring continued quality is challenging, especially when customer satisfaction is the provided service. It seems to become easier with new technologies like Artificial Intelligence. However, field data are necessary to ...