A Taguchi-based Kansei engineering study of mobile phones at product design stage

This article is aimed at applying Taguchi method in Kansei engineering and explores a way to integrate it into an industrial product design stage. Emotional customer needs are derived using Kansei image word pairs. The Taguchi-based approach is validated by a case study with mobile phones. Experimental work in implementing the proposed approach was able to suggest design attributes of a mobile phone that are essential to be considered at the product design stage to satisfy the customers’ expectations and hence to increase the company's sales.

[1]  Asil Oztekin,et al.  A decision support system for usability evaluation of web-based information systems , 2011, Expert Syst. Appl..

[2]  David A. Huffman,et al.  A method for the construction of minimum-redundancy codes , 1952, Proceedings of the IRE.

[3]  Bernard Yannou,et al.  Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics , 2004 .

[4]  Yukihiro Matsubara,et al.  An analysis of Kansei structure on shoes using self-organizing neural networks , 1997 .

[5]  P. Vyncke Lifestyle Segmentation , 2002 .

[6]  Chung-Hsing Yeh,et al.  User-oriented design for the optimal combination on product design , 2006 .

[7]  Charles H. Fine Clockspeed: Winning Industry Control In The Age Of Temporary Advantage , 1998 .

[8]  Min Xie,et al.  An integrated approach to innovative product development using Kano’s model and QFD , 2000 .

[9]  Hiromitsu Takagi,et al.  Interactive evolutionary computation: Cooperation of computational intel-ligent and human kansei , 1998 .

[10]  Chung-Hsing Yeh,et al.  Consumer-oriented product form design based on fuzzy logic: A case study of mobile phones , 2007 .

[11]  Jennifer Blackhurst,et al.  PCDM: a decision support modeling methodology for supply chain, product and process design decisions , 2005 .

[12]  Selim Zaim,et al.  UWIS: An assessment methodology for usability of web-based information systems , 2009, J. Syst. Softw..

[13]  J. H. Myers Segmentation and Positioning for Strategic Marketing Decisions , 1996 .

[14]  Simon Schütte,et al.  Integrating Kansei Engineering and QFD in Product development , 2001 .

[15]  P. Herbig,et al.  Global markets and the new product development process , 1996 .

[16]  K. G. Swift,et al.  Design for assembly , 1983 .

[17]  Chung-Hsing Yeh,et al.  Form design of product image using grey relational analysis and neural network models , 2005, Comput. Oper. Res..

[18]  Jussi Angesleva,et al.  Evolutionary computation in creative design , 2001 .

[19]  S. Hoekstra,et al.  Integral Logistic Structures: Developing Customer-Oriented Goods Flow , 1992 .

[20]  Mitsuo Nagamachi,et al.  Rule-based inference model for the Kansei Engineering System , 1999 .

[21]  Alastair Macdonald,et al.  Aesthetic intelligence: Optimizing user-centred design , 2001 .

[22]  A. H. Redford,et al.  Design for Assembly , 1983, Methods and Tools for Computer Integrated Manufacturing.

[23]  Asil Oztekin,et al.  UseLearn: A novel checklist and usability evaluation method for eLearning systems by criticality metric analysis , 2010 .

[24]  Simon Schütte,et al.  Designing Feelings into Products : Integrating Kansei Engineering Methodology in Product Development , 2002 .

[25]  S. Carliner,et al.  Physical , Cognitive , and Affective : A Three-part Framework for Information Design , 2000 .

[26]  Peter R. Dickson,et al.  Market Segmentation, Product Differentiation, and Marketing Strategy , 1987 .

[27]  Mitsuo Nagamachi,et al.  Kansei Engineering: A new ergonomic consumer-oriented technology for product development , 1995 .

[28]  Roger Jianxin Jiao,et al.  A Kansei mining system for affective design , 2006, Expert Syst. Appl..

[29]  Jonathan Cagan,et al.  Quantifying Aesthetic Form Preference in a Utility Function , 2009 .

[30]  Hefin Rowlands,et al.  Methods and techniques to help quality function deployment (QFD) , 2000 .