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Innovative product design based on customer requirement weight calculation model

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Abstract

In the processes of product innovation and design, it is important for the designers to find and capture customer’s focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.

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References

  1. X. H. Du, J. X. Jiao, M. M. Tseng. Understanding customer satisfaction in product customization. The International Journal of Advanced Manufacturing Technology, vol. 31, no. 3–4, pp. 396–406, 2006.

    Article  Google Scholar 

  2. C. K. Kwong, H. Bai. A fuzzy AHP approach to the determination of importance weights of customer requirements in quality function deployment. Journal of Intelligent Manufacturing, vol. 13, no. 5, pp. 367–377, 2002.

    Article  Google Scholar 

  3. H. H. Wu, A. Y. H. Liao, P. C. Wang. Using grey theory in quality function deployment to analyse dynamic customer requirements. The International Journal of Advanced Manufacturing Technology, vol. 25, no. 11–12, pp. 1241–1247, 2005.

    Article  Google Scholar 

  4. A. Mousavi, P. Adl, R. T. Rakowski, A. Gunasekaran. Design of a production planning system using customer oriented design and resource utilisation (CODARU). The International Journal of Advanced Manufacturing Technology, vol. 17, no. 11–12, pp. 805–809, 2001.

    Article  Google Scholar 

  5. A. H. Awang, X. T. Yan. Development of a support system for customer requirement capture. Global Design to Gain a Competitive Edge, Springer, Chapter 1, pp. 71–80, 2008.

  6. H. H. Wu, J. I. Shieh. Using a Markov chain model in quality function deployment to analyse customer requirements. The International Journal of Advanced Manufacturing Technology, vol. 30, no. 1–2, pp. 141–146, 2006.

    Article  Google Scholar 

  7. J. I. Shieh, H. H. Wu. Applying a hidden Markov chain model in quality function deployment to analyze dynamic customer requirements. Quality and Quantity, vol. 43, no. 4, pp. 635–644, 2009.

    Article  Google Scholar 

  8. S. S. Xia, L. Y. Wang. Customer requirements mapping method based on association rule mining for mass customization. Journal of Shanghai Jiaotong University (Science), vol. 13, no. 3, pp. 291–296, 2008.

    Article  Google Scholar 

  9. Y. T. Chong, C. H. Chen. Customer needs as moving targets of product development: A review. The International Journal of Advanced Manufacturing Technology, vol. 48, no. 1–4, pp. 395–406, 2010.

    Article  Google Scholar 

  10. C. H. Chen, L. P. Khoo, W. Yan. Evaluation of multicultural factors from elicited customer requirements for new product development. Research in Engineering Design, vol. 14, no. 3, pp. 119–130, 2003.

    Article  Google Scholar 

  11. X. Lai, M. Xie, K. C. Tan, B. Yang. Ranking of customer requirements in a competitive environment. Computers & Industrial Engineering, vol. 54, no. 2, pp. 202–214, 2008.

    Article  Google Scholar 

  12. Y. L. Li, J. F. Tang, X. G. Luo, J. Xu. An integrated method of rough set, Kano’s model and AHP for rating customer requirements’ final importance. Expert Systems with Applications, vol. 36, no. 3, pp. 7045–7053, 2009.

    Article  Google Scholar 

  13. C. H. Chen, L. P. Khoo, W. Yan. A strategy for acquiring customer requirement patterns using laddering technique and ART2 neural network. Advanced Engineering Informatics, vol. 16, no. 3, pp. 229–240, 2002.

    Article  Google Scholar 

  14. Y. J. Lv. Weight calculation method of fuzzy analytical hierarchy process. Fuzzy Systems and Mathematics, vol. 16, no. 2, pp. 79–85, 2002. (in Chinese)

    Google Scholar 

  15. A. K. Verma, R. Anil, O. P. Jain. Fuzzy logic based group maturity rating for software performance prediction. International Journal of Automation and Computing, vol.4, no. 4, pp. 406–412, 2007.

    Article  Google Scholar 

  16. X. Y. Luo, Z. H. Zhu, X. P. Guan. Adaptive fuzzy dynamic surface control for uncertain nonlinear systems. International Journal of Automation and Computing, vol.6, no. 4, pp. 385–390, 2009.

    Article  Google Scholar 

  17. J. J. Zhang. Fuzzy analytical hierarchy process. Fuzzy Systems and Mathematics, vol. 14, no. 2, pp. 80–88, 2000. (in Chinese)

    Google Scholar 

  18. A. F. Guneri, M. Cengiz, S. Seker. A fuzzy ANP approach to shipyard location selection. Expert Systems with Applications, vol. 36, no. 4, pp. 7992–7999, 2009.

    Article  Google Scholar 

  19. M. Y. Ma, C. Y. Chen, F. G. Wu. A design decision-making support model for customized product color combination. Computers in Industry, vol. 58, no. 6, pp. 504–518, 2007.

    Article  Google Scholar 

  20. T. C. Wang, Y. H. Chen. Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP. Information Sciences, vol. 178, no. 19, pp. 3755–3765, 2008.

    Article  MATH  MathSciNet  Google Scholar 

  21. F. Herrera, L. Martinez, A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems, vol. 8, no. 6, pp. 746–752, 2000.

    Article  MathSciNet  Google Scholar 

  22. T. N. Deura, T. Matsunaga, R. O. Suzuki, K. Ono, M. Wakino. Titanium powder production by TiCl4 gas injection into magnesium through molten salts. Metallurgical and Materials Transactions B, vol. 29, no. 6, pp. 1167–1174, 1998.

    Article  Google Scholar 

  23. C. G. Guo, Y. X. Liu, P. Tian. Fuzzy comprehensive evaluation method of the importance ratings of customers’ requirements. In Proceedings of the 6th CIRP-sponsored International Conference on Digital Enterprise Technology, Springer, vol. 66, pp. 361–373, 2010. (to be published)

    Article  Google Scholar 

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Correspondence to Chen-Guang Guo.

Additional information

This work was supported by Major National Science and Technology Special Projects during the 10th five-year plan (No. 2006BAF01A19), Key Scientific and Technological Project of Liaoning Province (No. 2006219008), Key Scientific and Technological Project of Shenyang City (No. 1071114-2-00).

Chen-Guang Guo received the B. Sc. degree in communication and transportation engineering from Shenyang Jianzhu University, Shenyang, PRC, and M. Sc. degree in mechanical manufacturing and automation from Northeastern University, PRC in 2005 and 2008, respectively. He is currently a Ph. D. candidate at Northeastern University, PRC.

His research interests include product innovation design, digital manufacturing, CAD/CAE, and product lifecycle management.

Yong-Xian Liu is a full professor in Institute of Advanced Manufacturing and Automation Technology of Northeastern University, vice director-general of Institute of Advanced Manufacturing and Automation Technology, winner of the State Council Special Subsidy, chief engineer of the CAD/CAM Engineering Technology Center of Liaoning province and vice directorgeneral of CAD/CAM academic committee of the national metallurgical system.

His research interests include CAD/CAM technology and integration, manufacturing systems, new structure machine tools, and computerized numerical control (CNC) systems and simulation.

Shou-Ming Hou received the B. Sc. degree in mechanical engineering from Jiaozuo Mining Institute, PRC in 1993, and M. Sc. degree in mechanical engineering from Huazhong University of Science and Technology, in 2000. Now, he is a Ph.D. candidate in the Department of Mechanical Engineering and Automation at Northeastern University, PRC. In 1993, he was a faculty member of Jiaozuo Mining Institute, PRC. Currently, he is an associate professor in the Department of Computer Science and Technology, at Henan Polytechnic University, PRC.

His research interests include product data management, collaborative design, and virtual reality.

Wei Wang received the B. Sc. degree in mechanical engineering from Shenyang University of Technology, PRC in 2007, and M. Sc. degree in mechanical engineering from Northeastern University, PRC in 2009. Now, she is a Ph.D. candidate at Northeastern University.

Her research interests include CAD/CAE, manufacturing system, and laser rapid prototyping.

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Guo, CG., Liu, YX., Hou, SM. et al. Innovative product design based on customer requirement weight calculation model. Int. J. Autom. Comput. 7, 578–583 (2010). https://doi.org/10.1007/s11633-010-0543-3

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  • DOI: https://doi.org/10.1007/s11633-010-0543-3

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