Study of consumer behaviors for product design and redesign
In order to stay competitive in businesses, companies started adopting Kansei Engineering methodologies studying the psychological behaviour of consumers on product designs. For this reason, the author proposed a methodology capable of generating concepts from the user-selected product attribute v...
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Format: | Final Year Project |
Language: | English |
Published: |
2009
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Online Access: | http://hdl.handle.net/10356/18992 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | In order to stay competitive in businesses, companies started adopting Kansei
Engineering methodologies studying the psychological behaviour of consumers on
product designs. For this reason, the author proposed a methodology capable of generating concepts from the user-selected product attribute values and integrating optional Kansei(s) into the recommended design parameters. In the integration processes, relationships between the Kanseis and the product attribute values as well as the interactions between Kanseis were addressed. The objective of this project is to provide designers with a convenient program application capable of generating design concepts with consideration of the consumer’s emotions and affections.
Genetic algorithm, a randomised search and optimization technique guided by the
principles of evolution and natural genetics, was used in the concept generation.
Regarding the weightings on the relationships between the Kanseis and the product attribute values as well as the interaction between the Kanseis, the values were determined by surveys conducted on 50 undergraduates and a discussion with 5
industrial design students respectively. The trial tests on the program application
revealed that a tight fitness margin produces the best estimated results whereas a
lower fitness margin allows a wide range of diverse designs. With measures taken to
prevent improper designs, it can be concluded that the feasibility and accuracy of the proposed methodology depends heavily on the accuracy of the product attribute
values’ fitness. The fitness margin determines the strength of the design parameters. |
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