Study on a Correlation Model between the Kansei Image and the Texture Harmony

Abstract

Texture harmony pursues a suitable texture matching to meet the customers Kansei image requirements. The texture harmony method which is based on Kansei Engineer is developed. Several questionnaires are made to obtain the Kansei words, design elements and texture factors. The representative Kansei words, representative design elements and the representative texture factors are selected using Pareto Diagram, Likert scale, multidimensional scaling analysis and cluster analysis. After developing the virtual samples, the respondents are asked to evaluate the Kansei image score of each sample according to the different Kansei image word. The Kansei image evaluating matrix is obtained by combining the Kansei image score with the texture combination code. The multiple linear regression model is supposed to explain the relationship of the Kansei image score and the texture factors. Based on the Kansei image evaluate matrix, the hypothesis is verified using the SPSS software. The case of electric kettle texture harmony design is studied to verify the method. The method can facilitate designers work, and lay a foundation of computer aided texture design system.