A Hybrid Kansei Design Expert System Using Artificial Intelligence

Authors:
Jyun-Sing Chen;Kun-Chieh Wang;Jung-Chin Liang
Affiliations:
Department of technological Product Design, Ling Tung University, Taichung City, Taiwan, R.O.C 40852;Department of technological Product Design, Ling Tung University, Taichung City, Taiwan, R.O.C 40852;Department of technological Product Design, Ling Tung University, Taichung City, Taiwan, R.O.C 40852
Venue:
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Year:
2008

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Abstract

This paper aims to propose a novel approach for high heel design using the integral schemes of Kansei engineering and grey-based artificial intelligence. First, to meet the market's needs, the Kansei engineering scheme is adopted in order to translate the customer's preferences into the product's form elements. Secondly, to speed up and enhance the translation performance, the grey system theory and radial basis function neural network schemes are used. Thirdly, a bi-directional evaluation hybrid Kansei engineering system is constructed via the aforementioned methodology. Finally, a form design expert system is proposed in consideration of designer's usage. To illustrate the functions of the proposed design expert system, an example of the development of new high heels is demonstrated.