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Affective product form design using fuzzy Kansei engineering and creativity

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Abstract

How to design an affective product form meeting customer’s requirements always draws much attention. In the past, a popular scheme “Kansei Engineering” was widely and successfully used in dealing with such kind of issue. However, among vast Kansei studies, none of them concerned on the most important matter in product form design: creativity. In the first place, this study proposes a new Kansei manipulation procedure in which it combines an associative creativity thinking process with the fuzzy Kansei engineering to explore a new product form matching future customers’ requirements. A horn speaker is selected as the demonstration target. In the fuzzy Kansei process, totally four final Kansei images were obtained via market survey and statistical analysis. Seven design elements were obtained via product decomposition. Then the 7-scale semantic differential scheme and fuzzification are used to quantify the qualitative properties of product image and design element respectively. A Kansei evaluation was done to 30 subjects for 19 selected samples. Based on the obtained evaluation data, the multi-linear regression and back-propagation neural network schemes are adopted to build the relationship between Kansei words and design elements. In the creative form generation process, the obtained Kansei outcomes were used as the design basis and an associative creativity thinking procedure merging with biological simulation forming. It includes six steps which is applied to develop a new product form. In the end, a verification test was performed and a satisfying result of 11.7 % has been increased in customer satisfaction.

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References

  • Akao Y (1990) History of quality function deployment in Japan. Hanser Publishers, Germany

  • Baek S, Hwang M, Chung H, Kim P (2008) Kansei factor space classified by information for Kansei image modeling. Appl Math Comput 205:874–882

    MATH  Google Scholar 

  • Chen CC, Chung MC (2008) Integrating the Kano model into a robust design approach to enhance customer satisfaction with product design. Int J Prod Econ 114:667–681

    Article  Google Scholar 

  • Cohen L (1995) Quality function deployment How to make QFD work for you. Addison-Wesley, Massachusetts

    Google Scholar 

  • Cross N (2000) Engineering design methods: strategies for product design. Wiley, Chichester

    Google Scholar 

  • Elias C, John C (2005) Creative system design methodologies: the case of complex technical systems. Technovation 25:831–840

    Article  Google Scholar 

  • Green EP, Srinivasan V (1978) Conjoint analysis in consumer research: issues and outlook. J Consum Res 5(2):103–123

    Article  Google Scholar 

  • Huang MS, Tsai HC, Huang TH (2011) Applying Kansei engineering to industrial machinery trade show booth design. Int J Ind Ergon 41:72–78

    Article  Google Scholar 

  • Ishihara S, Ishihara K, Nagamachi M, Matsubara Y (1995) An automatic builder for a Kansei engineering expert system using self-organizing neural networks. Int J Ind Ergon 15(1):13–24

    Article  Google Scholar 

  • Jang JSR, Sun CT, Mizutani E (1997) Neural-fuzzy and soft computing. Prentice-Hall Inc., Simon & Schuster/A Viacom Company, U.S.

  • Michael N (2005) Artificial intelligence. A guide to intelligent system. Addison Wesley, Pearson Education Limited, U.S.

  • Nagamachi M (1995) Kansei engineering: a new ergonomic consumer-oriented technology for product development. Int J Ind Ergon 15(1):3–11

    Article  MathSciNet  Google Scholar 

  • Nagamachi M (1996) Introduction of Kansei engineering. Japan Standard Association, Tokyo

    Google Scholar 

  • Nigel C (2001) Creativity in the design process:co-evolution of problem-solution. Des Stud 22(5):425–437

    Article  Google Scholar 

  • Osgood CE, Tannenbaum PH, Suci GJ (1957) The measurement of meaning. University of Illinois Press, Urbana

    Google Scholar 

  • Tormod N, Tone EN (2002) Creative design-an efficient tool for product development. Food Qual Prefer 15:97–104

    Google Scholar 

  • Yang CC (2011) Constructing a hybrid Kansei engineering system based on multiple affective responses: application to product form design. Comput Ind Eng 60:760–768

    Article  Google Scholar 

Download references

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Correspondence to Kun-Chieh Wang.

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Shen, HC., Wang, KC. Affective product form design using fuzzy Kansei engineering and creativity. J Ambient Intell Human Comput 7, 875–888 (2016). https://doi.org/10.1007/s12652-016-0402-3

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