A QFD-enabled product conceptualisation approach via design knowledge hierarchy and RCE neural network

  • Authors:
  • Wei Yan;Li Pheng Khoo;Chun-Hsien Chen

  • Affiliations:
  • Logistics Engineering School, Shanghai Maritime University, 1550 Pudong Dadao, Shanghai 200135, PR China;School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, Singapore 639798;School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, Singapore 639798

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2005

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Abstract

In this paper, an approach that attempts to improve conventional quality function deployment (QFD) technique in terms of effective design knowledge handling in product concept development is proposed and described. For this purpose, a QFD-enabled product conceptualisation system was established. It consists of three cohesively interacting modules, namely, design knowledge elicitation module using laddering technique, design knowledge representation module using design knowledge hierarchy (DKH), and design knowledge organisation module using restricted Coulomb energy (RCE) neural network. A case study on wood golf club design was used to illustrate the performance of the proposed approach. From the case study, the prototype QFD-enabled product conceptualisation system has demonstrated its effectiveness in design knowledge acquisition, representation and organisation at an early stage of NPD. The details of the validation are discussed.