scholarly journals Kansei Engineering Analysis of Purple-clay Teapot Based on Online Comment Data

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Xinyu ZHANG ◽  
Bin QI ◽  
Yanpu YANG ◽  
Xiaoming SUN

Product form has become an important communication medium between designers and consumers. Therefore, the collection and analysis of consumer evaluation of products can provide an important reference index for product form design. In this paper, purple-clay teapot was taken as an example and comments of Tmall consumers were collected through web crawler, and the product image vocabulary was extracted to analyze the needs of users. Using the research method of Kansei Engineering, the semantic space of the modeling and image of purple-clay teapot was established, and the relationship between the modeling elements and the image of purple-clay teapot was searched, which could provide valuable reference for the modeling design of purple-clay teapot.

2013 ◽  
Vol 274 ◽  
pp. 513-516 ◽  
Author(s):  
Yu Qing Xu ◽  
Kun Chen ◽  
Hai Bin Qin ◽  
Zhao Yang Wang

Design mode of product form is constructed combining Kansei Engineering (KE) with Ergonomics. KE is used as main technique to transform consumers' feelings and images of shape, size, material, operability of product into design form futures. The main factors and problems of Kansei experiment and Kansei analysis are also identified.Ergonomics acts as the assisting technique for meeting physiological criteria of consumer group. An implement of a product form design was conducted, and then the feasibility of proposed design mode based on KE is discussed which provides related products’ reference to designers.


Author(s):  
José E. Lugo ◽  
Stephen M. Batill ◽  
Laura Carlson

Engineers describe design concepts using design variables. Users develop their visual judgment of products by mentally grouping design variables according to Gestalt principles, extracting meaning using semantic dimensions and attaching attributes to the products, as reflected in Kansei methodology. The goal of this study was to assess how these different sources of information and representations of product form (design variables, Gestalt variables, Kansei attributes, and semantic dimensions) could combine to best predict product preference for both designers and users. Sixteen wheel rim designs were created using four design variables that were also combined into higher-order Gestalt variables. Sixty-four participants viewed each rim, and rated it according to semantic dimensions and Kansei attributes, and provided an overall “like” rating. The most reliable prediction of product preference were developed using Gestalt variables in combination with the meaning and emotion the users attached to the product. Finally, implications for designers are discussed.


Sign in / Sign up

Export Citation Format

Share Document