Application of Kansei Engineering and Association Rules Mining in Product Design
The Kansei engineering is a technology which
converts human feelings into quantitative terms and helps designers
develop new products that meet customers- expectation. Standard
Kansei engineering procedure involves finding relationships between
human feelings and design elements of which many researchers have
found forward and backward relationship through various soft
computing techniques. In this paper, we proposed the framework of
Kansei engineering linking relationship not only between human
feelings and design elements, but also the whole part of product, by
constructing association rules. In this experiment, we obtain input
from emotion score that subjects rate when they see the whole part of
the product by applying semantic differentials. Then, association
rules are constructed to discover the combination of design element
which affects the human feeling. The results of our experiment
suggest the pattern of relationship of design elements according to
human feelings which can be derived from the whole part of product.
[1] K. Krippendorff, The Semantic Turn, A New Foundation for Design. FL:
CRC Press, 2006, pp. 5-8.
[2] M. Nagamachi, Kansei/Affective Engineering. FL: CRC Press, 2011, pp.
3-5.
[3] C. Tanoue, K. Ishizaka, and M. Nagamachi, "Kansei Engineering: A
study on perception of vehicle interior image," International Journal of
Industrial Ergonomics, Vol. 19, pp. 115-128, 1997.
[4] S. Ishihara, K. Ishihara, M. Nagamachi, and Y. Matsubara, "An analysis
of Kansei structure on shoes using self-organizing neural networks,"
International Journal of Industrial Ergonomics, Vol. 19, pp. 93-104,
1997.
[5] H. Lai, Y. Lin, C. Yeh, and C. Wei, "User-oriented design for the
optimal combination on product design," International Journal
Production Economics, Vol. 100, pp. 253-267, 2006.
[6] T. Jindo, K. Hirasago, and M. Nagamachi, "Development of a design
support system for office chairs using 3-D graphic," International
Journal of Industrial Ergonomics, Vol. 15, pp. 49-62, 1995.
[7] M. Nagamachi, Kansei/Affective Engineering. FL: CRC Press, 2011, pp.
51-225.
[8] M. Nagamachi, "Kansei Engineering: A new ergonomic consumeroriented
technology for product development," International Journal of
Industrial Ergonomics, Vol. 15, pp. 3-11, 1995.
[9] M. Nagamachi, Kansei/Affective Engineering. FL: CRC Press, 2011, pp.
31-225.
[10] C. Osgood, C. Suci, P. Tannenbaum, The measurement of Meaning.
Urbana: University of Illinois Press, 1957, pp. 76-124.
[11] C. Maurer, C. Overbeke, G. Smets, The semantics of street furniture. In:
Susann Vihma (Eds.), Object and Images - Studies in Design and
Advertising. University of Industrial Arts Helsinki UIAH, pp. 86-93.
[12] H. Espe, Symbolic qualities of watches. In: Susann Vihma (Eds.), Object
and Images - Studies in Design and Advertising. University of Industrial
Arts Helsinki UIAH, pp. 124-131.
[13] H. Shang, C. Ming, C. Chien, "A semantic differential study of designer-
and users- product form perception," International Journal of Industrial
Ergonomics, Vol. 25, pp.375-391, 2000.
[14] T. Jindo, K. Hirasago, "Application studies to car interior of Kansei
engineering," Industrial Journal of Industrial Ergonomics, Vol. 19, pp.
105-114, 1997.
[15] S. Ishihara, et al., "An automatic builder for a Kansei Engineering
expert system using self-organizing neural networks," International
Journal of Industrial Ergonomics, Vol. 15, pp. 13-24, 1995.
[16] Y. Lin, H. Lai, C. Yeh, "Consumer-oriented product form design based
on fuzzy logic: A case study of mobile phones," International Journal of
Industrial Ergonomics, Vol. 37, pp. 531-543, 2007.
[17] J. Park, S. Han, "A fuzzy rule-based approach to modeling affective user
satisfaction towards office chair design," International Journal of
Industrial Ergonomcis, Vol. 34, pp. 31-47, 2004.
[18] T. Tsuchiya, et al., "A fuzzy rule induction method using genetic
algorithm," International Journal of Industrial Ergonomics," Vol. 18, pp.
135-145, 1996.
[19] M. Purdy, "The structure of the visual world: Space-perception and the
perception of wholes," The Psychological Review, Vol. 42, 399-424,
1935.
[20] C. Yang, "Constructing a hybrid Kansei engineering system based on
multiple affective responses: Application to product form design,"
Computer & Industrial Engineering, Vol. 60, pp. 760-768, 2011.
[21] K. Nakada, "Kansei engineering research on the design of construction
machinery," International Journal of Industrial Ergonomics, Vol. 19, pp.
129-146, 1997.
[22] S. Baek, M. Hwang, H. Chung, P. Kim, "Kansei factor space classified
by information for Kansei image modeling," Applied Mathematics and
Computation, Vol. 205, pp. 874-882, 2008.
[23] H. Chen, Y. Chang, "Extraction of product form features critical to
determining consumers- perceptions of product image using a numerical
definition-based systematic approach," International Journal of
Industrial Ergonomics, Vol. 39, pp. 133-145, 2009.
[24] B. Lawson, How designers think: the design process demystified.
Oxford: Architectural Press, 2005.
[25] D. Berlyne, Structure and Direction in thinking. New York: John Wiley,
1965.
[26] M. Wertheimer, Productive Thinking. New York: Harper and Row,
1959.
[27] A. De Groot, Thought and Choice in Chess. The Hauge: Mouton, 1965.
[28] W. Garner, Uncertainty and Structure as Psychological concepts. New
York: Jone Wiley, 1962.
[29] K. Krippendorff, The Semantic Turn, A New Foundation for Design. FL:
CRC Press, 2006, pp. 5-8.
[30] P. Bloch, "Seeking the Ideal Form: Product Design and Consumer
Response," Journal of Marketing, Vol. 59, pp. 16-29, 1995.
[31] J. Jiao, J. Zhang, Y. Halander, "A Kansei mining system for affective
design," Expert System with Application, Vol. 30, pp. 658-673, 2006.
[32] X. Yang, D. Wu, F. Zhou, J. Jiao, "Association Rule Mining for
Affective Product Design," Proceedings of the 2008 IEEE IEEM, 2008.
[33] P. Moen, Data Mining Methods. University of Helsinki. Spring 2005.
[1] K. Krippendorff, The Semantic Turn, A New Foundation for Design. FL:
CRC Press, 2006, pp. 5-8.
[2] M. Nagamachi, Kansei/Affective Engineering. FL: CRC Press, 2011, pp.
3-5.
[3] C. Tanoue, K. Ishizaka, and M. Nagamachi, "Kansei Engineering: A
study on perception of vehicle interior image," International Journal of
Industrial Ergonomics, Vol. 19, pp. 115-128, 1997.
[4] S. Ishihara, K. Ishihara, M. Nagamachi, and Y. Matsubara, "An analysis
of Kansei structure on shoes using self-organizing neural networks,"
International Journal of Industrial Ergonomics, Vol. 19, pp. 93-104,
1997.
[5] H. Lai, Y. Lin, C. Yeh, and C. Wei, "User-oriented design for the
optimal combination on product design," International Journal
Production Economics, Vol. 100, pp. 253-267, 2006.
[6] T. Jindo, K. Hirasago, and M. Nagamachi, "Development of a design
support system for office chairs using 3-D graphic," International
Journal of Industrial Ergonomics, Vol. 15, pp. 49-62, 1995.
[7] M. Nagamachi, Kansei/Affective Engineering. FL: CRC Press, 2011, pp.
51-225.
[8] M. Nagamachi, "Kansei Engineering: A new ergonomic consumeroriented
technology for product development," International Journal of
Industrial Ergonomics, Vol. 15, pp. 3-11, 1995.
[9] M. Nagamachi, Kansei/Affective Engineering. FL: CRC Press, 2011, pp.
31-225.
[10] C. Osgood, C. Suci, P. Tannenbaum, The measurement of Meaning.
Urbana: University of Illinois Press, 1957, pp. 76-124.
[11] C. Maurer, C. Overbeke, G. Smets, The semantics of street furniture. In:
Susann Vihma (Eds.), Object and Images - Studies in Design and
Advertising. University of Industrial Arts Helsinki UIAH, pp. 86-93.
[12] H. Espe, Symbolic qualities of watches. In: Susann Vihma (Eds.), Object
and Images - Studies in Design and Advertising. University of Industrial
Arts Helsinki UIAH, pp. 124-131.
[13] H. Shang, C. Ming, C. Chien, "A semantic differential study of designer-
and users- product form perception," International Journal of Industrial
Ergonomics, Vol. 25, pp.375-391, 2000.
[14] T. Jindo, K. Hirasago, "Application studies to car interior of Kansei
engineering," Industrial Journal of Industrial Ergonomics, Vol. 19, pp.
105-114, 1997.
[15] S. Ishihara, et al., "An automatic builder for a Kansei Engineering
expert system using self-organizing neural networks," International
Journal of Industrial Ergonomics, Vol. 15, pp. 13-24, 1995.
[16] Y. Lin, H. Lai, C. Yeh, "Consumer-oriented product form design based
on fuzzy logic: A case study of mobile phones," International Journal of
Industrial Ergonomics, Vol. 37, pp. 531-543, 2007.
[17] J. Park, S. Han, "A fuzzy rule-based approach to modeling affective user
satisfaction towards office chair design," International Journal of
Industrial Ergonomcis, Vol. 34, pp. 31-47, 2004.
[18] T. Tsuchiya, et al., "A fuzzy rule induction method using genetic
algorithm," International Journal of Industrial Ergonomics," Vol. 18, pp.
135-145, 1996.
[19] M. Purdy, "The structure of the visual world: Space-perception and the
perception of wholes," The Psychological Review, Vol. 42, 399-424,
1935.
[20] C. Yang, "Constructing a hybrid Kansei engineering system based on
multiple affective responses: Application to product form design,"
Computer & Industrial Engineering, Vol. 60, pp. 760-768, 2011.
[21] K. Nakada, "Kansei engineering research on the design of construction
machinery," International Journal of Industrial Ergonomics, Vol. 19, pp.
129-146, 1997.
[22] S. Baek, M. Hwang, H. Chung, P. Kim, "Kansei factor space classified
by information for Kansei image modeling," Applied Mathematics and
Computation, Vol. 205, pp. 874-882, 2008.
[23] H. Chen, Y. Chang, "Extraction of product form features critical to
determining consumers- perceptions of product image using a numerical
definition-based systematic approach," International Journal of
Industrial Ergonomics, Vol. 39, pp. 133-145, 2009.
[24] B. Lawson, How designers think: the design process demystified.
Oxford: Architectural Press, 2005.
[25] D. Berlyne, Structure and Direction in thinking. New York: John Wiley,
1965.
[26] M. Wertheimer, Productive Thinking. New York: Harper and Row,
1959.
[27] A. De Groot, Thought and Choice in Chess. The Hauge: Mouton, 1965.
[28] W. Garner, Uncertainty and Structure as Psychological concepts. New
York: Jone Wiley, 1962.
[29] K. Krippendorff, The Semantic Turn, A New Foundation for Design. FL:
CRC Press, 2006, pp. 5-8.
[30] P. Bloch, "Seeking the Ideal Form: Product Design and Consumer
Response," Journal of Marketing, Vol. 59, pp. 16-29, 1995.
[31] J. Jiao, J. Zhang, Y. Halander, "A Kansei mining system for affective
design," Expert System with Application, Vol. 30, pp. 658-673, 2006.
[32] X. Yang, D. Wu, F. Zhou, J. Jiao, "Association Rule Mining for
Affective Product Design," Proceedings of the 2008 IEEE IEEM, 2008.
[33] P. Moen, Data Mining Methods. University of Helsinki. Spring 2005.
@article{"International Journal of Business, Human and Social Sciences:62745", author = "Pitaktiratham J. and Sinlan T. and Anuntavoranich P. and Sinthupinyo S.", title = "Application of Kansei Engineering and Association Rules Mining in Product Design", abstract = "The Kansei engineering is a technology which
converts human feelings into quantitative terms and helps designers
develop new products that meet customers- expectation. Standard
Kansei engineering procedure involves finding relationships between
human feelings and design elements of which many researchers have
found forward and backward relationship through various soft
computing techniques. In this paper, we proposed the framework of
Kansei engineering linking relationship not only between human
feelings and design elements, but also the whole part of product, by
constructing association rules. In this experiment, we obtain input
from emotion score that subjects rate when they see the whole part of
the product by applying semantic differentials. Then, association
rules are constructed to discover the combination of design element
which affects the human feeling. The results of our experiment
suggest the pattern of relationship of design elements according to
human feelings which can be derived from the whole part of product.", keywords = "Association Rules Mining, Kansei Engineering,
Product Design, Semantic Differentials", volume = "6", number = "9", pages = "2451-6", }