Modeling Product Form Preference Using Gestalt Principles, Semantic Space, and Kansei

2012 ◽  
Author(s):  
José E. Lugo ◽  
Stephen M. Batill ◽  
Laura Carlson
Keyword(s):  
Semantic Space ◽  
Product Form ◽  
Sources Of Information ◽  
Gestalt Principles ◽  
Design Concepts ◽  
Design Variables ◽  
Form Design ◽  
Product Form Design ◽  
Different Sources ◽  
Product Preference

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.

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
Keyword(s):  
Semantic Space ◽  
Product Form ◽  
Kansei Engineering ◽  
Web Crawler ◽  
Consumer Evaluation ◽  
Product Image ◽  
Form Design ◽  
Product Form Design ◽  
Reference Index ◽  
The Relationship

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.

scholarly journals Application of Fuzzy-Based Hybrid Taguchi Method for Multiobjective Optimization of Product Form Design

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Yongfeng Li ◽  
Meng-Dar Shieh ◽  
Chih-Chieh Yang ◽  
Liping Zhu
Keyword(s):  
Taguchi Method ◽  
Robust Design ◽  
Affective Response ◽  
Affective Responses ◽  
Product Form ◽  
Design Approach ◽  
Characteristic Index ◽  
Design Variables ◽  
Form Design ◽  
Product Form Design

In today’s competitive market, industrial product form design is moving towards being consumer centric. Affective responses relate to customers’ affective needs and are receiving increasing attention. To design a product form that can appeal to consumers, designers should consider multiple affective responses (MARs). This paper proposes a robust design approach that uses a fuzzy-based hybrid Taguchi method to derive the optimal product form design concerning MARs. First, design analysis is used to identify design variables and MARs. According to the results, a Taguchi experiment is designed in which fuzzy sets are used to measure the MARs; then, signal-to-noise (S/N) ratios are calculated. Subsequently, a fuzzy questionnaire with multiple answers is employed to acquire consumers’ preference weights for MARs, following which Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is adopted to transform the multiple S/N ratios into a multiperformance characteristic index (MPCI). On the basis of the MPCI, the effects of design variables are identified through analysis of variance and the response table and the response graph are obtained. Consequently, the optimal form design is achieved. A car profile design was used as an example to demonstrate the proposed approach. The results indicate that this approach can effectively improve consumers’ affective response qualities and can be used as a robust design approach to optimize product form design.

Study on the Application of Kansei Engineering in Product Form Design

2013 ◽  
Vol 274 ◽  
pp. 513-516 ◽  
Author(s):  
Yu Qing Xu ◽  
Kun Chen ◽  
Hai Bin Qin ◽  
Zhao Yang Wang
Keyword(s):  
Product Form ◽  
Kansei Engineering ◽  
Consumer Group ◽  
Main Technique ◽  
Form Design ◽  
Main Factors ◽  
Product Form Design

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.

A neural network based approach for product form design

2002 ◽  
Vol 23 (1) ◽  
pp. 67-84 ◽  
Author(s):  
Shih-Wen Hsiao ◽  
H.C Huang
Keyword(s):  
Neural Network ◽  
Product Form ◽  
Form Design ◽  
Product Form Design
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