A dominance-based rough set approach to Kansei Engineering in product development

Keen competitions in the global market have led product development to a more knowledge-intensive activity than ever, which requires not only tremendous expert knowledge but also effective analysis of design information. Kansei Engineering as a customer-oriented methodology for product development, often has to analyse imprecise design information inherent with nonlinearity and uncertainty. This paper proposes a systematic approach to Kansei Engineering based on the dominance-based rough set theory. Two novel concepts known as category score and partition quality have been developed and incorporated into the proposed approach. The new approach proposed is able to identify and analyse two types of inconsistencies caused by indiscernibility relations and dominance principles respectively. The result of an illustrative case study shows that the proposed approach can effectively extract Kansei knowledge from imprecise design information, and it can be easily integrated into an expert system for customer-oriented product development.

[1]  Yukihiro Matsubara,et al.  An analysis of Kansei structure on shoes using self-organizing neural networks , 1997 .

[2]  Tomio Jindo,et al.  Application studies to car interior of Kansei engineering , 1997 .

[3]  Catherine C. Marshall,et al.  Designing Qualitative Research , 1996 .

[4]  Simon Schütte,et al.  Engineering Emotional Values in Product Design : Kansei Engineering in Development , 2005 .

[5]  Katsuari Kamei,et al.  Kansei and colour harmony models for townscape evaluation , 2006 .

[6]  Yukihiro Matsubara,et al.  An automatic builder for a Kansei Engineering expert system using self-organizing neural networks , 1995 .

[7]  Yukihiro Matsubara,et al.  A method for learning decision tree using genetic algorithm and its application to Kansei engineering system , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[8]  Yukihiro Matsubara,et al.  A fuzzy rule induction method using genetic algorithm , 1996 .

[9]  Masayuki Takatera,et al.  On‐demand production system of apparel on the basis of Kansei engineering , 2004 .

[10]  Akira Harada,et al.  Design Based on Kansei , 2002 .

[11]  Hideyoshi Yanagisawa,et al.  Interactive Design Support System by Customer Evaluation and Genetic Evolution: Application to Eye Glass Frame , 2003, KES.

[12]  Li Pheng Khoo,et al.  An investigation into affective design using sorting technique and Kohonen self-organising map , 2006, Adv. Eng. Softw..

[13]  Bernard Yannou,et al.  Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics , 2004 .

[14]  Mitsuo Nagamachi,et al.  Concepts, methods and tools in Kansei engineering , 2004 .

[15]  Z. Pawlak Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[16]  Mitsuo Nagamachi,et al.  Kansei engineering and application of the rough sets model , 2006 .

[17]  Masao Arakawa,et al.  Kansei design using genetic algorithms , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[18]  Salvatore Greco,et al.  Rough approximation of a preference relation by dominance relations , 1999, Eur. J. Oper. Res..

[19]  Mitsuo Nagamachi,et al.  Kansei Engineering: A new ergonomic consumer-oriented technology for product development , 1995 .

[20]  Hideo Tanaka,et al.  Variable Precision Bayesian Rough Set Model and Its Application to Kansei Engineering , 2008, Trans. Rough Sets.

[21]  Gretchen B. Rossman,et al.  Designing qualitative research, 3rd ed. , 1999 .

[22]  Mitsuo Nagamachi,et al.  Kansei engineering as a powerful consumer-oriented technology for product development. , 2002, Applied ergonomics.

[23]  Mitsuo Nagamachi An image technology expert system and its application to design consultation , 1991, Int. J. Hum. Comput. Interact..

[24]  K. Okuhara,et al.  Extraction of relationship among Kansei words by expert system using rough set analysis , 2005, Proceedings of the 2005 International Conference on Active Media Technology, 2005. (AMT 2005)..

[25]  Salvatore Greco,et al.  Rough approximation by dominance relations , 2002, Int. J. Intell. Syst..