This paper presents a multi-response optimization method that uses the grey-based Taguchi method as the integrative product form design optimization method, and it serves as a tool for product form design to determine the optimal combination of design parameters in Kansei engineering (KE). This method is unique in that it combines the Taguchi method (TM) and grey relational analysis (GRA), allowing it to take advantage of the benefits of both methods. The TM is used to design experiments and generate combinative product form design samples which can be used to improve product quality. The GRA is applied to multi-response optimization problems. Factor effect analysis and analysis of variance (ANOVA) are used to determine which combinations of design parameters will result in the optimal product design. To demonstrate the applicability of the grey-based TM, a case study of a car form design is presented, and a confirmation test is performed to verify the performance of the optimal product design. The results show that the grey-based TM can deal with optimization problems with multiple Kansei responses and determine an optimal car form design that is representative of the consumers' perception in a systematic manner. The confirmation test results also show that the optimal product design generated by the grey-based TM can be used to improve the overall quality of a product form.
Nowadays, consumers have become more selective in choosing products not only deciding based on its functionality and its value but also on its aesthetic and emotional value. Aesthetic and emotional values have thus become important aspects in the success of a product in a competitive market. Consequently, recognizing the primary parameters used to generate combinative product shape which has the ability to evoke a particular emotion should be given strong consideration. This paper describes the application of robust design approach which allows the designer to determine the optimal design parameters to obtain form impression evoked by a product shape feature. A Taguchi’s orthogonal array method is applied to design the experiment and is analyzed to obtain the optimal parameters for each factor. ANOVA is then employed to identify the most significant factors. A Taguchi’s L18orthogonal array was adopted for an experiment on the design of an office chair. The case study contains six three-level factors, and 18 different combinative design samples created from shape parameters. The results of the experiment shows that it is possible to create a design support system that can facilitates the designer in the creative process by suggesting shape parameters relating to a specific form impression.
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