Baby Cradle Design with Kansei Knowledge Mining Based on Rough Set Theory

Abstract

Today, producing consumer-oriented products are a key to commercial success. The successful companies have to aim to capture consumer’s psychological perception. Kansei Engineering is a type of methodology to determine consumer’s perception on product elements for using new product development. Kansei evaluation dataset were significantly developed such as uncertainty reason techniques including rough set, fuzzy set and neural networks. In literature, the rough set theory has been widely used approach to reduce the complexity of the knowledge database. In this chapter, to extract more accurate design parameters and Kansei knowledge, rough set rule based mining was applied for Kansei engineering research to baby cradle design. The proposed design methodology results show that obtained rules are consistent with customer expectations.