Soliciting customer requirements for product redesign based on picture sorts and ART2 neural network

Authors:
Meng-Dar Shieh;Wei Yan;Chun-Hsien Chen
Affiliations:
Department of Industrial Design, National Cheng Kung University, 1 University Road, Tainan 701, Taiwan;Logistics Engineering School, Shanghai Maritime University, 1550 Pudong Dadao, Shanghai 200135, PR China;School of Mechanical and Aerospace Engineering, Nanyang Technological University, North Spine (N3), Level 2, 50 Nanyang Avenue, Singapore 639798, Singapore
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

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Abstract

Design knowledge acquisition plays an extremely important role in new product conceptualization and product redesign. This study aims at facilitating the effectiveness of product redesign activities. It involves two interrelated phases, namely customer requirements elicitation and customer requirements evaluation. Sorting techniques, picture sorts in particular, have been employed for customer requirements acquisition during product redesign process. By applying such a systematic knowledge or requirements acquisition technique, some objectives and constraints of product redesign can then be identified. Furthermore, it has become an imperative to quantitatively and automatically analyze the elicited customer requirements so as to simplify and optimize the subsequent product conceptualization and selection of conceptual design alternatives. For this purpose, the adaptive resonance theory, especially ART2, neural network has been utilized for the preliminary design decisions, such as customer segmentation, in terms of customer requirements evaluation. A case study on the mobile hand phone redesign is used to demonstrate and validate this approach.