Abstract
Today, product design has been much more complicated when compared with the past. Shorter product life cycle increased product development cost. In order to stay competitive in the market, a well-designed product should be able to not only meet functionality requirements, but also satisfy consumers’ psychological needs (or feelings). In this study, a rough set based kansei engineering decision support system was developed using Fuzzy AHP (Analytical Hierarchical Process) and PLS (Partial Least Square) approximations. Decision rules for 16 design samples were generated by orthogonal design. Twelve selected samples were tested whether the decision of customers were true or not related with the sample products in terms of taste of customers. We find that qualitative evaluations for product design in kansei engineering are more consistent with the results of consumers rather than quantitative evaluations.
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