Design candidate identification using neural network-based fuzzy reasoning

Conceptual design has profound impact on success of a product design. Ident ification of the best conceptual design candidate is a crucial step as desi gn information is not complete and design knowledge is minimal at conceptua l design stage. This paper presents a method for design candidate evaluatio n and identification using neural network-based fuzzy reasoning. The method consists of the following steps: (1) acquisition of customer needs and ran king of their importance, (2) establishment of measurable metrics and their relations with customer needs, (3) development of design specifications an d initial evaluation of design candidates, and (4) evaluation and identific ation of design candidates based on design specifications and customer need s using neural network-based fuzzy reasoning. A case study is given to show the effectiveness of the proposed method and associated algorithms. (C) 20 00 Elsevier Science Ltd. All rights reserved.