On the other hand; one of the core technologies in Kansei Engineering (KE) is to identify the relational rules between design elements of products and human evaluation data such as sense and feeling (Nagamachi; 1996). Rough set methods have been used to extract decision rules between human Kansei evaluation experimental data set and design elements (Nishino; 2001; 2003). The extracted rules would enable product designer to design the products fitted to the sense of human.
The purpose of this paper is to apply Rough Sets lower / upper approximations for the definition of decision rules for the design elements of beer cans and compare them to the results obtained through statistical analysis of same experimental data set. Data sets from 2 previous studies in Japan and Mexico were used (Hirata; 2004a; 2004b).
Keywords: Product design; Rough set theory; Consumer feeling (Kansei); package design; Kansei market segmentation