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Proceedings of CAD'17, 2017, 22-26
Method for Grouping of Customers and Aesthetic Design Based on Rough Set Theory
Abstract. Due to maturation of science and technology, it becomes increasingly difficult to differentiate products in terms of performance, functional feature or price. Therefore, companies are required to differentiate their products in terms of subjective and abstract qualities such as aesthetic and comfort that are evaluated by customer’s feeling, which is called “Kansei” in Japanese. The quality evaluated by customer kansei is called “Kansei quality”. In the field of emotional engineering or kansei engineering, the methods for measuring customer kansei or the impression of products have been developed and applied to many case studies. In these methods, semantic differential method (SD method) is widely used. In addition, various methods for supporting aesthetic design by utilizing measured customer kansei have also been developed. These methods generate a new aesthetic design which a customer prefers best by analyzing the relationships between the results of customer’s kansei evaluation of existing products and their aesthetic elements. Most of industrial products are geared toward many customers, not a single customer, and it is quite difficult to design a product that satisfy all customers due to the diversity of their kansei. To overcome such problem, robust design methods using Taguchi method and grouping methods were proposed.
Keywords. Kansei engineering, Aesthetic design, Grouping, Hierarchical clustering analysis, Rough set theory