A Method for Reducing Fuzziness and Accelerating New Product Modelling in CAD : the case of Design for Manufacturing
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nadège Troussier
Author: Bluntzer, Jean-Bernard; Barret, Régis; Ostrosi, Egon
Series: ICED
Institution: Université de Technologie de Belfort-Montbéliard, France
Section: Design Methods
Page(s): 0263-0272
DOI number: https://doi.org/10.1017/pds.2023.27
ISBN: -
ISSN: -
Abstract
Improvements in product development can increase the competitiveness of firms. However, new product development in CAD systems involves difficulties and uncertainties that increase along with the pressure to develop the products. A distinct characteristic of CAD modeling for new product development is its uncertainty. This is because the information is usually approximate and incomplete during CAD modeling. Thus, the main objective of this paper is to propose a robust and flexible CAD approach to reduce uncertainty and accelerate new product modeling in the context of design for manufacturing. This methodology permits the convergence towards different product forms depending on the selected manufacturing process. Application of this approach has shown that when uncertainty is high, approving a complete CAD modeling results in a delay in product development. In contrast, CAD modeling using fuzzy models results in a gain of valuable development time because the model is completed when knowledge about manufacturing technologies, company fit and capabilities, and markets is available.
Keywords: Computer Aided Design (CAD), New product development, Design for X (DfX), Fuzzy modeling