Preliminary Study of Kansei Engineering (KE) for Societal Performance in Sustainable Product Design
Author(s) -
Mohd Fahrul Hassan,
Eka Ariefzakwan Annuar,
Sia Chee Kiong,
Mohd Azwir Azlan,
Mohd Nasrull Abdol Rahman,
Md Fauzi Ahmad
Publication year - 2019
Publication title -
iop conference series materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/607/1/012012
Subject(s) - kansei engineering , feeling , product (mathematics) , product design , kansei , population , new product development , marketing , statistical population , engineering , computer science , descriptive statistics , psychology , human–computer interaction , business , mathematics , social psychology , statistics , geometry , demography , sociology
Nowadays, product development indicates that a product’s success in the market is determined by the inclusion of consumer’s technical needs for product design. However, implicit feelings and impressions by the consumers is quite challenging because they cannot be externally assessed. Therefore, the makers aim to figure out the factors that contribute to the purchaser’s fulfilments of their product. This paper introduces indicators that can be used to fulfil consumers’ needs specifically to handle the implicit needs of consumers in sustainable product design based on Kansei Engineering (KE) approach. KE is a Japanese design method used to translate feelings into product parameters and was used to look at the car design features of a consumer’s dream car. Preferences of four design features (safety, conveniences, car interaction, and size of capacity) were explored in a sample population of sixty university students through questionnaires. Seven kanseis/feelings elicited by phones were determined to be important to this group: (1) Dynamic, (2) Easy, (3) Elegant, (4) Personality, (5) Positive physical traits, (6) Sophisticated, and (7) Technology. This study chooses to explore the use of Descriptive Statistical and Correlation Component Analysis for statistical significance of the data set as the main method of analysis to determine whether there is a significant difference between the car design features and between the society‘s rating of the car features through Kansei words. Utilizing the system will help another automobile plan that matches consumers’ needs to be proposed.
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