Prelude to Natphoric Kansei Engineering Framework

Anitawati Mohd Lokman, Mohammad Bakri Che Haron, Siti Zaleha Zainal Abidin, Noor Elaiza Abd Khalid, Shigekazu Ishihara

Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Malaysia.
Faculty of Psychological Science, Hiroshima International University, Hiroshima, Japan.

DOI: 10.4236/jsea.2013.612076                

Abstract

Consumers’ emotion has become imperative in product design. In affective design field, Kansei Engineering (KE) has been recognized as a technology that enables discovery of consumer’s emotion and formulation of guide to design products that win consumers in the competitive market. Albeit powerful technology, there is no rule of thumb in its analysis and interpretation process. KE expertise is required to determine sets of related Kansei and the significant concept of emotion. Many research endeavours become handicapped with the limited number of available and accessible KE experts. This work is performed to simulate the role of experts with the use of Natphoric algorithm and thus provides solution to the complexity and flexibility in KE. The algorithm is designed to learn the process by implementing training datasets taken from previous KE research works. A framework for automated KE is then designed to realize the development of automated KE system.

Keywords

Kansei Engineering; Ant Colony Clustering; Natphoric Algorithm; Computer-Aided KE

Conflicts of Interest

The authors declare no conflicts of interest.

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