The application of Kansei engineering and SDM based creativity to product form design

Abstract

The Kansei Engineering (KE) was widely used in determining the relationship between product images and their form elements. However, among vast studies about product design using KE, none concerned the most important issue in product design: creativity. In the first place, this study proposes a new Kansei manipulation procedure in which it combines the System Design Method (SDM) based creativity generation process with the fuzzy Kansei engineering to design a new product matching customers' requirements. A LED bike light is selected as the demonstration target. Totally four high-level Kansei images are obtained via market survey and statistical analysis. Seven design elements were obtained via product decomposition. Then the 7-sclae semantic differential scheme and fuzzification scheme are used to quantify the qualitative properties of product images and design elements respectively. A Kansei evaluation was done to 30 subjects for 18 selected samples. Based on the obtained evaluation data, the multi-linear regression and back-propagation neural network scheme are adopted to build the relationship between Kansei images and design elements. Then the above Kansei outcomes are used as the design reference and a SDM based creativity generation procedure is applied to develop a new product form. In the end, a verification test is performed. The last outcome shows the shark-type bike light enhance the customer preference by 19%.