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Study On Kansei Image Of Composite Material

Posted on:2017-08-20Degree:MasterType:Thesis
Country:ChinaCandidate:Y R BaiFull Text:PDF
GTID:2322330512467799Subject:Design
Abstract/Summary:PDF Full Text Request
With the development of science and technology, a variety of new products are emerging, how quickly set up the process of new product design and development, how to save development costs and improve design quality are all problems for designers. In addition to the emotional consumption is now characterized by emotional consumer age, consumers pursuit of spiritual feelings and emotional experience becomes more intense,while the emergence and development of Kansei Engineering provide new ideas for the research of Kansei. By means of Kansei Engineering, the vague uncertain emotional problems can be quantified and studied by engineering research methods. Today, Kansei engineering has been increasingly used in the field of research of material texture image.This topic is based on the common means of Kansei Engineering and the quantification I theory to discuss the Kansei image of collocation of different materials. The mathematic model for the analysis is developed to discuss quantitatively the relationship of collocation of different materials to the psychological kansei image of the consumers? The topic is divided into three stages:First,obtain the emotional information of users about different materials by Kansei Engineering,then process these information by filtering and hierarchical clustering analysis to get the representative material samples and Kansei vocabulary; The second stage is through questionnaire to find the kansei value of different material collocation; The third stage is through quantification I theory to establish prediction equation and find the incidence to kansei value of each ingredient in different material collocation, being a guidance of the matching of surface materials.
Keywords/Search Tags:Material Collocation, Kansei Engineering, Quantification ? Theory, Kansei Image
PDF Full Text Request
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