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

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.

[1]  Luis G. Occeña,et al.  CONDENSE: A concurrent design evaluation system for product design , 2001 .

[2]  William David Cockrell,et al.  Industrial Electronics Handbook , 1958 .

[3]  M.H. Hassoun,et al.  Fundamentals of Artificial Neural Networks , 1996, Proceedings of the IEEE.

[4]  Susan Carlson Skalak House of Quality , 2002 .

[5]  P. Huovila,et al.  Customer-oriented Design Methods for Construction Projects , 1998 .

[6]  Jinxing Xie,et al.  An intelligent hybrid system for customer requirements analysis and product attribute targets determination , 1998 .

[7]  Abdul Rahman Omar,et al.  An intelligent information framework relating customer requirements and product characteristics , 2001 .

[8]  T. Saaty The Seven Pillars of the Analytic Hierarchy Process , 2001 .

[9]  Li Pheng Khoo,et al.  An integrated approach to the elicitation of customer requirements for engineering design using picture sorts and fuzzy evaluation , 2002, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[10]  Charles H. Fine,et al.  Time Versus Market Orientation in Product Concept Development: Empirically-Based Theory Generation , 1997 .

[11]  D. N. Hinkle The change of personal constructs from the viewpoint of a theory of construct implications , 1965 .

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  Li Pheng Khoo,et al.  An investigation on a prototype customer-oriented information system for product concept development , 2002, Comput. Ind..

[14]  Nigel Shadbolt,et al.  A comparison of sorting techniques in knowledge acquisition , 1992 .

[15]  Li Pheng Khoo,et al.  A strategy for acquiring customer requirement patterns using laddering technique and ART2 neural network , 2002, Adv. Eng. Informatics.

[16]  J. Hauser,et al.  The House of Quality , 1988 .

[17]  G. Kelly The Psychology of Personal Constructs , 2020 .

[18]  Jack B. Revelle,et al.  The QFD handbook , 1998 .

[19]  N. Kano,et al.  Attractive Quality and Must-Be Quality , 1984 .

[20]  Li Pheng Khoo,et al.  A Radial Basis Function Neural Network Multicultural Factors Evaluation Engine For Product Concept Development , 2001, Expert Syst. J. Knowl. Eng..

[21]  Chun-Hsien Chen,et al.  A knowledge sorting process for a product design expert system , 1999, Expert Syst. J. Knowl. Eng..

[22]  Ronald G. Day Quality Function Deployment: Linking a Company With Its Customers , 1993 .