Prelude to Natphoric Kansei Engineering Framework


Consumers’ emotion has become imperative in product design. In affective design field, Kansei Engineering (KE) has been recognized as a technology that enables discovery of consumer’s emotion and formulation of guide to design products that win consumers in the competitive market. Albeit powerful technology, there is no rule of thumb in its analysis and interpretation process. KE expertise is required to determine sets of related Kansei and the significant concept of emotion. Many research endeavours become handicapped with the limited number of available and accessible KE experts. This work is performed to simulate the role of experts with the use of Natphoric algorithm and thus provides solution to the complexity and flexibility in KE. The algorithm is designed to learn the process by implementing training datasets taken from previous KE research works. A framework for automated KE is then designed to realize the development of automated KE system.

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A. Lokman, M. Haron, S. Abidin, N. Khalid and S. Ishihara, "Prelude to Natphoric Kansei Engineering Framework," Journal of Software Engineering and Applications, Vol. 6 No. 12, 2013, pp. 638-644. doi: 10.4236/jsea.2013.612076.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] J. Rajasekera and S. Dayal, “Using Kansei Engineering with New JIT to Accomplish Cost Advantage,” International Journal of Biometrics, Vol. 2, No. 2, 2010, pp. 163-172. 2010.031795
[2] N. Mitsuo, “Perspectives and New Trend of Kansei/Affective Engineering,” 1st European Conference on Affective Design and Kansei Engineering & 10th QMOD Conference, University of Linkoping and Lund University, Helsingborg, 2007.
[3] H. M. Khalid, “Conceptualizing Affective Human Factors Design,” Theoretical Issues in Ergonomics Science, Vol. 5, No. 1, 2004, pp. 1-3.
[4] M. Nagamachi, I. Ishihara, A. M. Lokman, T. Nishino, M., Matsubara, T. Tsuchiya, et al., “Kansei/Affective Engineering,” Taylor & Francis Group, CRC Press, 2010. EBK1439821336
[5] M. Nagamachi, “Kansei Engineering and Its Method,” Management System, Vol. 2, No. 2, 1992, pp. 97-105.
[6] S. Schutte and J. Eklund, “Rating scales in Kansei Engineering,” Internationcal Conference on Kansei Engineering and Emotion Research 2010, KEER2011, Paris, 2010, pp. 23-25.
[7] M. Nagamachi and A. M. Lokman, “Innovations of Kansei Engineering. Industrial Innovation Series,” Taylor & Francis, Florida, 2010.
[8] L. Lin and C. Xue, “Review of Research and Development Of Computer-Aided Kansei Engineering,” Frontiers of Mechanical Engineering in China, Springer, 2009.
[9] J. Jiao, Y. Zhang and M. Helander, “A Kansei Minig system for Affective Design,” Journal of Expert Systems with Applications, Vol. 30, No. 4, 2006, pp. 658-673.
[10] M. Nagamachi, “Workshop 2 on Kansei Engineering,” Proceedings of International Conference on Affective Human Factors Design, Singapore, 2001.
[11] H. Yanagisawa and S. Fukuda, “Development of Interactive Industrial Design Support System Considering Customer’s Evaluation,” JSME International Journal, Vol. 47, No. 2, 2004, pp. 762-769.
[12] M. Nagamachi, “Kansei Engineering: A Powerful Ergonomic Technology for Product Development,” In: Proceedings of the International Conference on Affective Human Factors Design, Asean Academic Press, London, 2001, pp. 9-14.
[13] K. M. Nasser and T. Marjan, “Design with Emotional Approach by Implementing Kansei Engineering—Case Study: Design of Kettle,” International Conference on Kansei Engineering and Emotion Research, KEER2010, Paris, 2010, pp. 625-632.
[14] M. Nagamachi, “Kansei Engineering: The Implication and Applications to Product Development,” IEEE International Conference on SMC, 1999, pp. 273-278.
[15] A. M. Lokman, “Design & Emotion: The Kansei Engineering Methodology,” Malaysian Journal of Computing, Vol. 1, No. 1, 2010, pp. 1-11.
[16] A. M. Lokman, “Emotional User Experience in Web Design: The Kansei Engineering Approach,” Univerisiti Teknologi MARA, 2009.
[17] A. M. Lokman, N. L. M. Noor and M. Nagamachi, “Expert Kansei Web: A Tool to Design Kansei Website, Enterprise Information Systems,” Springer, Berlin, Heidelberg, 2009.
[18] Y. Shimizu, T. Sadoyama, M. Kamijo, S. Hosaya, M. Hashimoto, T. Otani, K. Yokoi, Y. Horiba, M. Taketera, M. Honywood and S. Inui, “On-Demand Production Systems of Apparel on Basis on Kansei Engineering,” International Journal of Clothing Science and Technology, Vol. 16, No. 1/2, 2004, pp. 32-42.
[19] R. R. Seva, H. B. Duh and M. G. Helander, “The Marketing Implications of Affective Product Design,” Journal of Applied Ergonomics, Vol. 38, No. 6, 2007, pp. 723-731.
[20] A. M. Lokman and M. Nagamachi, “Validation of Kansei Engineering Adoption in e-Commerce Web Design,” Kansei Engineering International, 2009.
[21] M. Nagamachi, “Kansei Engineering: An Ergonomic technology for a Product Development,” Proceedings of IEA’94, 1994, pp. 120-122.
[22] T. Childs, A. de Pennington, J. Rait, T. Robins, K. Jones, C. Workman, S. Warren and J. Colwill, “Affective Design (Kansei Engineering) in Japan, Faraday Packaging Partnership,” University of Lees, UK, 2001.
[23] A. Lanzotti and P. Tarantino, “Kansei Engineering Approach for Total Quality Design and Continuous Innovation,” The TQM Journal, Vol. 20, No. 4, 2008, pp. 324-337.
[24] T. Murai, “Large Rough Sets and Modal Logics,” Journal of Japan Society for Fuzzy Theory and Systems, Vol. 13, No. 5, 2001, pp. 23-32.
[25] L. Hultman and S. Larsson, “Development of a Method for Subjective Expert Evaluation of the Human Driving Geometry,” Lulea University of Technology, Lulea, 2005.
[26] N. R. Council, et al., “Council Computer-Aided Materials Selection during Structural Design,” The National Academies Press, Washington, DC, 1995.
[27] D. E. Culler and W. Burd, “A Framework for Extending Computer Aided Process Planning to Include Business Activities and Computer Aided Design and Manufacturing (CAD/CAM) Data Retrieval,” Robotics and Computer-Integrated Manufacturing, Vol. 23, No. 3, 2007, pp. 339-350.
[28] V. Raman and A. Palanissamy, “Computer Aided Legal Support System: An Initial Framework for Retrieving Legal Cases by Case Base Reasoning Approach,” Innovations in Information Technology, Vol. 2, No. 48, 2008, pp. 317-321.
[29] D. S. Kim, D. H. Baek and W. C. Yoon, “Development and Evaluation of a Computer-Aided System for Analyzing Human Error in Railway Operations,” Reliability Engineering and System Safety, Vol. 95, No. 2, 2010, pp. 87-98.
[30] H. W. Hsiao and E. Liu, “A Neurofuzzy—Evolutionary Approach for Product Design,” Integrated ComputerAided Engineering, Vol. 11, No. 4, 2004, pp. 323-338.
[31] H. W. Hsiao and H. C. Tsai, “Applying a Hybrid Approach Based on Fuzzy Neural Network and Genetic Algorithm to Product Form Design,” International Journal of Industrial Ergonomics, Vol. 35, No. 5, 2005, pp. 411-428.
[32] Y. Kinoshita, S. Ichinohe, Y. Sakakura, E. W. Cooper and K. Kamei, “Kansei Product Design for the Active Senior Generation—A Case Study of Mobile Phone Designs,” International Conference on Kansei Engineering and Emotion Research, 2007.
[33] K. C. Wang, “A Hybrid Kansei Engineering Design Expert System Based on Grey System Theory and Support Vector Regression,” Expert Systems with Applications, Vol. 38, No. 7, 2011, pp. 8738-8750.
[34] D. Floreano and C. Mattiussi, “Bio-Inspired Artificial Intelligence Theories, Methods and Technologies,” MTI Press, 2008.
[35] X. Cui Swarm, “Intelligence in Text Document Clustering,” Oak Ridge National Laboratory, 2009.
[36] E. Bonabeau, M. Dorigo and G. Theraulaz, “Swarm intelligence: From natural to artificial intelligence,” Oxford University Press, New York, 1999.
[37] G. Martens, C. L. Poppe and R. V. Walle, “Unsupervised Texture Segmentation and Labeling Using Biologically Inspired Features, Multimedia Signal Processing,” IEEE 10th Workshop, 2008.
[38] R. Chiong, “Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering,” 2009.
[39] N. Tsimboukakis and G. Tambouratzis, “Word Map Systems for Content-Based Document Classification,” IEEE Transactions on Systems, Man & Cybernetics—Part C, 2011, pp. 662-673.
[40] S. G. Khode and R. Bhatia, “Improving Retrieval Effectiveness Using Ant Colony Optimization,” International Conference on Advances in Computing, Control, & Telecommunication Technologies, 2009, pp. 737-741.
[41] Z. S. Xu et al., “The Study on Electric Power System Based on Swarm Intelligence,” Advanced Materials Research, Vol. 442, 2012, pp. 424-429.

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