Abstract
The role of aesthetic design is increasing in the development of industrial products with growing maturity of product functions. Designers are required to reflect consumer preference in aesthetic design under the consideration of use and function. Effective techniques which enable designers to identify preference and need of customers are indispensable. This study thus aims to construct a design support system which identify them and provide ideas to a designer at an early stage in the design process. In the identification of consumer preference, it is necessary to expose vague consumer preference. The design support system also aims to reduce a burden to consumers for a preference survey and extract consumer preference by using rough sets and the genetic algorithm. The use of rough sets works well for effective analysis from small amount of data, and can extract preference rules of consumers. Furthermore, the constructed system is able to automatically create multiple design solutions by reflecting the consumer preference rules on design solutions created by a designer, and to display the created solutions to the designer.
