Study on product form design via Kansei engineering and virtual reality

Abstract

It is very important to predict the reaction of customers to future products. Sample pictures and line sketches are commonly used for discovering consumers’ demands. However, these two agents are difficult to express the real product form clearly and comprehensively, which may affect the accuracy of consumer affection prediction. In this paper, a method based on Kansei engineering via virtual reality (VR) has been proposed to construct a mapping relationship between form elements and consumer affection from four dimensions of the overall, unit, interrelation, and detail (OUID), so as to provide references for product form design. The correlation between product form elements and the perceptual image was studied with multiple linear regression analysis and partial correlation analysis. The different effects of VR, sketches, and pictures on user affection prediction were compared in this paper as well. A hairdryer has been employed as an example to illustrate the proposed method. The results show that compared with sketch and picture, VR based-prediction model is more accurate and reliable in predicting users’ emotional preferences. In addition to the unit form, the overall features, interrelation, and details are also the key factors affecting consumer preference. Highlight Based on Kansei Engineering, this paper investigated the correlation between the form elements of the product and the user's affection via VR. The proposed approach can help designers to quickly and accurately capture the user's perceptual image and transform it into design elements. The different effects of VR, sketches, and pictures on customer affection prediction were compared. A decomposition model is proposed to analyse the product form elements on four dimensions (overall features, unit form, interrelation, and details).