Consumers' Kansei Needs Clustering Method for Product Emotional Design Based on Numerical Design Structure Matrix and Genetic Algorithms.

Yan-pu Yang,Sui-huai Yu,Rong Gu,Yu-feng Gu,Deng-kai Chen

doi:10.1155/2016/5083213

Abstract

Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.

Highlights

Companies that listen to their consumers are more likely to be successful in the market [1, 2]
Kansei engineering consists of five types [4, 13]: (1) category classification for identifying consumer’s affective need with a tree structure; (2) Kansei engineering system (KES), a computer aided system with mathematically statistical tools to connect Kansei and product properties; (3) hybrid engineering system, incorporating KES and Kansei prediction elicited by product properties; (4) Kansei engineering modeling for assessing consumers’ feeling of Kansei words; (5) virtual Kansei engineering with a virtual reality system for presenting products and standard data collection systems
A novel method for consumers’ Kansei needs clustering method based on numerical design structure matrix (NDSM) and genetic algorithms is proposed in this work

Summary

Introduction

Companies that listen to their consumers are more likely to be successful in the market [1, 2]. Consumers buy products for basic function and usability, and for emotional experiences that could be evoked by attractive product appearance [9]. When coming to product design, involving emotional elements in product design could make a product attractive and evoke positive emotions [11]. In this regard, Kansei engineering [4, 5] has been developed as a comprehensive psychological and ergonomic consumeroriented technique to help designers to link consumers’ emotional response to design properties of a product [12]. Kansei engineering has been successfully applied in various fields of product design, such as alarm clock [14], sunglasses [15], digital camera [16], mobile phone [17], and domestic commodities [18]

Methods

Findings

Discussion

Conclusion