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Decision Support System for Industrial Designer Based on Kansei Engineering

  • Fu Guo
  • Long Ren
  • Zhenke He
  • Haiying Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6775)

Abstract

A combination of the traditional methodology of Kansei Engineering with the up-to-date Decision Support System (DSS) is developed in this paper. The users who have a little knowledge of information technology can achieve the Kansei Engineering optimal design in a short period of time by using the DSS, which is composed of a friendly human-computer interface, a database management module and a model management section. The introduction of the structure of the DSS is made first and a case study on the flat-panel handset is followed. Through the use of morphological analysis and semantic differential method, many designed samples and Kansei words are stored in the pre-determined database module. Some more consumers’ information is required to get the evaluations of the automatic-formed models. Then a combination of BP artificial networks and GA is used to get the final results. The system is developed by the PHP language to make sure that it runs smoothly in a web environment. Finally, a matrix of physical parameters is attained according to the output of the system. A decoding procedure is done to get the real physical design elements of the optimal model of handset, followed by a prototyping method using other software such as UG. The optimal design is shown at last.

Keywords

Kansei Engineering Decision Support System flat-panel handset 

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References

  1. 1.
    Hong, S.W., Han, S.H., Kim, K.J.: Optimal balancing of multiple affective satisfaction dimensions: a case study on mobile phones. International Journal of Industrial Ergonomics 38(3-4), 272–279 (2008)CrossRefGoogle Scholar
  2. 2.
    Chang, C.C.: Factors influencing visual comfort appreciation of product form of digital cameras. International Journal of Industrial Ergonomics 38(11), 1007–1016 (2008)CrossRefGoogle Scholar
  3. 3.
    Artacho-Ramirez, M.A., Diego-Mas, J.A., Alcaide-Marzal, J.: Influence of the model graphical representation on the perception of product aesthetic and emotional features: an exploratory study. International Journal of Industrial Ergonomics 38(11), 942–952 (2008)CrossRefGoogle Scholar
  4. 4.
    Nagamachi, M.: Kansei Engineering: an intelligent system in product development. In: 1994 Japan-U.S.A. Symposium on Flexible Automation-A Pacific Rim Conference, vol. 2, pp. 537–540 (1994)Google Scholar
  5. 5.
    Nomura, J.: Consumer decision support system in virtual space using Kansei Engineering. JIPDEC Informatization Quarterly (101), 77–87 (1995)Google Scholar
  6. 6.
    Sato, N., Anse, M., Tabe, T.: A method for constructing a movie-selection support system based on Kansei engineering. J. Human Interface and the Management of Information, 526–534 (2007)Google Scholar
  7. 7.
    Ishihara, S., Ishihara, K., Matsubara, Y., Nagamachi, M.: Self-organizing neural networks in Kansei engineering expert system. In: Proceedings of 11th European Conference on Artificial Intelligence, ECAI 1994, pp. 231–235 (1994)Google Scholar
  8. 8.
    Ishihara, S., Nagamachi, M., Ishihara, K.: Neural networks Kansei expert system for wrist watch design. In: The Sixth International Conference on Human-Computer Interactions Google Scholar
  9. 9.
    Basheera, I.A., Hajmeerb, M.: Artificial neural networks: fundamentals, computing, design, and application. Journal of Microbiological Methods 43, 3–31 (2000)CrossRefGoogle Scholar
  10. 10.
    Pearson, J.M., Shim, J.P.: An empirical investigation into DSS structures and environments. J. Decision Support Systems 13, 141–158 (1995)CrossRefGoogle Scholar
  11. 11.
    Chalmers, P.A.: The role of cognitive theory in human–computer interface. J. Computers in Human Behavior 19, 593–607 (2003)CrossRefGoogle Scholar
  12. 12.
    Lin, Y.C., Lai, H.H., Yeh, C.H.: Consumer-oriented product form design based on fuzzy logic: A case study of mobile phones. International Journal of Industrial Ergonomics 37, 531–543 (2007)CrossRefGoogle Scholar
  13. 13.
    Chuang, M.C., Chang, C.C., Hsu, S.H.: Perceptual elements, underlying user preferences toward product form of mobile phones. International Journal of Industrial Ergonomics 27, 247–258 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fu Guo
    • 1
  • Long Ren
    • 1
  • Zhenke He
    • 1
  • Haiying Wang
    • 1
  1. 1.Department of Management Science and Engineering, School of Business AdministrationNortheastern UniversityShenyangP.R. China

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