Application of Robust Design Approach for Design Parameterization in Kansei Engineering

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Abstract:

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 L18 orthogonal 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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Advanced Materials Research (Volumes 479-481)

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1670-1680

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February 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] S. Achiche and S. Ahmed, Mapping shape geometry and emotions using fuzzy logic, Proc. ASME 2008 Int Design Eng Tech Conf & Comput and Inform in Eng Conf (New York, USA 2008).

DOI: 10.1115/detc2008-49290

Google Scholar

[2] D.A. Norman, Emotional Design: Why We Love (or Hate) Everyday Things, Basic Books, New York, 2004.

Google Scholar

[3] P.H. Bloch, Seeking the ideal form: product design and consumer response, J Market. 59 (1995) 16-29.

Google Scholar

[4] M. Nagamachi, Perspectives and the new trend of kansei/affective engineering, TQM J. 20 (2008) 290-298.

DOI: 10.1108/17542730810881285

Google Scholar

[5] M. Nagamachi, Kansei/Affective Engineering, CRC Press., Boca Raton, FL, 2011.

Google Scholar

[6] M. Nagamachi and A.M. Lokman, Innovations of Kansei Engineering, CRC Press., Boca Raton, FL, 2011.

Google Scholar

[7] S. Schütte and J. Eklund, Product Development for Heart and Soul, Linköping Univ., Sweden, 2003.

Google Scholar

[8] S. Schütte, Engineering Emotional Values in Product Design: Kansei Engineering in Development, Doctoral Thesis, Linköpings Univ., Linköping, Sweden, 2005.

Google Scholar

[9] M.C. Chuang, C.C. Chang and S.H. Hsu, Perceptual factors underlying user preferences toward product form of mobile phones, Int J Indus Ergo. 27 (2001) 247-258.

DOI: 10.1016/s0169-8141(00)00054-8

Google Scholar

[10] H.H. Lai, Y.C. Lin, C.H. Yeh and C.H. Wei, User-oriented design for the optimal combination on product design, Int J Prod Econ. 100 (2006) 253-267.

DOI: 10.1016/j.ijpe.2004.11.005

Google Scholar

[11] Y.C. Lin, H.H. Lai and C.H. Yeh, Consumer-oriented product form design based on fuzzy logic: a case study of mobile phones, Int J Indus Ergo. 37 (2007) 531-543.

DOI: 10.1016/j.ergon.2007.03.003

Google Scholar

[12] S.W. Hsiao and H.C. Huang, A neural network based approach for product form design, Design Stu. 23 (2002) 67-84.

DOI: 10.1016/s0142-694x(01)00015-1

Google Scholar

[13] S.W. Hsiao, F.Y. Chiu and S.H. Lu, Product-form design model based on genetic algorithms, Int J Indus Ergo. 40 (2010) 237-246.

Google Scholar

[14] G. Taguchi, S. Chowdhury and Y. Wu, Taguchi's Quality Engineering Handbook, John Wiley & Sons, Inc., New Jersey, 2005.

Google Scholar

[15] M. Nalbant, H. Gökkaya and G. Sur, Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning, Mater Des. 28 (2007) 1379-1385.

DOI: 10.1016/j.matdes.2006.01.008

Google Scholar

[16] M. Kurt, E. Bagci and Y. Kaynak, Application of Taguchi ethods in the optimization of cutting parameters for surface finish and hole diameter accuracy in dry drilling processes, Int J Adv Manufg Tech. 40 (2009) 458-469.

DOI: 10.1007/s00170-007-1368-2

Google Scholar

[17] A.J. Mian, N. Driver and P.T. Mativenga, Identification of factors that dominate size effect in micro-machining, Int J Mach Tools Manuf. 51 (2011) 383-394.

DOI: 10.1016/j.ijmachtools.2011.01.004

Google Scholar

[18] R.A. Kishore, R. Tiwari, A. Dvivedi and I. Singh, Taguchi analysis of the residual tensile strength after drilling in glass fiber reinforced epoxy composites, Mater Des. 30 (2009) 2186-2190.

DOI: 10.1016/j.matdes.2008.08.035

Google Scholar

[19] S. Thipprakmas and W. Phanitwong, Process parameter design of spring-back and spring-go in V-bending process using Taguchi technique, Mater Des. 32 (2011) 4430-4436.

DOI: 10.1016/j.matdes.2011.03.069

Google Scholar

[20] J. Antony, D. Perry, C.B. Wang and M. Kumar, An application of Taguchi method of experimental design for new product design and development process, Assemb Automa. 26 (2006) 18-24.

DOI: 10.1108/01445150610645611

Google Scholar

[21] M. Arvidsson and I. Gremyr, Principles of robust design methodology, Qual & Reliab Eng Int. 24 (2008) 23-35.

DOI: 10.1002/qre.864

Google Scholar

[22] J.G. Cherng, M. Eksioglu and K. Kızılaslan, Vibration reduction of pneumatic percussive rivet tools: mechanical and ergonomic re-design approaches, Appl Ergo. 40 (2009) 256-266.

DOI: 10.1016/j.apergo.2008.04.011

Google Scholar

[23] H.H. Lai, Y.M. Chang and H.C. Chang, A robust design approach for enhancing the feeling quality of a product: a car profile case study, Int J Indus Ergo. 35 (2005) 445-460.

DOI: 10.1016/j.ergon.2004.10.008

Google Scholar

[24] C.C. Chen and M.C. Chuang, Integrating the kano model into a robust design approach to enhance customer satisfaction with product design, Int J Prod Econ. 114 (2008) 667-681.

DOI: 10.1016/j.ijpe.2008.02.015

Google Scholar

[25] P. Tarantino, A Statistical Thinking Approach to Kansei Engineering for Product Innovation, Doctoral Thesis, Univ. of Naples "Federico II", Naples, Italy, 2008.

Google Scholar