Evolution of Quality Function Deployment (QFD) via Fuzzy Concepts and Neural Networks
Quality Function Deployment (QFD) is an expounded, multi-step planning method for delivering commodity, services, and processes to customers, both external and internal to an organization. It is a way to convert between the diverse customer languages expressing demands (Voice of the Customer), and the organization-s languages expressing results that sate those demands. The policy is to establish one or more matrices that inter-relate producer and consumer reciprocal expectations. Due to its visual presence is called the “House of Quality" (HOQ). In this paper, we assumed HOQ in multi attribute decision making (MADM) pattern and through a proposed MADM method, rank technical specifications. Thereafter compute satisfaction degree of customer requirements and for it, we apply vagueness and uncertainty conditions in decision making by fuzzy set theory. This approach would propound supervised neural network (perceptron) for MADM problem solving.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1333640Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1628
 S. P. Bingulac, "On the compatibility of adaptive controllers (Published Conference Proceedings style)," in Proc. 4th Annu. Allerton Conf. Circuits and Systems Theory, New York, 1994, pp. 8-16.
 G. R. Faulhaber, "Design of service systems with priority reservation," in Conf. Rec. 1995 IEEE Int. Conf. Communications, pp. 3-8.
 W. D. Doyle, "Magnetization reversal in films with biaxial anisotropy," in 1987 Proc. INTERMAG Conf., pp. 2.2-1-2.2-6.
 Arash Shahin, 2005, "Quality Function Deployment: A Comprehensive Review," 2005.
 Richard Zultner, "Quality Function Deployment (QFD) for software," American Programmer, 1992.
 L .K . Chan, M .L .Wu, 2002. "Quality function deployment: A literature review," European Journal of Operational Research ,2002 ,pp. 143.
 K .J. Kim, H. Moskowitz, A. Dhingra, G. Evans, "Fuzzy multicriteria models for quality function deployment," European Journal of Operational Research, 2002, pp. 121, 504-518.
 H. Liu, F .Kong, "A new fuzzy MADM method : fuzzy RBF neural network model," LECTURE IN COMPUTER SCIENCE, 2006.
 F. Kong, H. Liu, "fuzzy RBF neural network model for multiple attribute decision making, " Lecture Notes in Computer Science, 2006.
 J. B. Yang, Y. M. Wang, D. L. XU, "the evidential reasoning approach for MADA under both probabilistic and fuzzy uncertainties," European Journal of Operational Research, 2006, pp. 171(1).
 Mr. Mehregan, H. Safari, "Combination of fuzzy TOPSIS and fuzzy ranking for multiattribute decision making," Lecture Notes in Computer Science, 2006.
 "Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator," European Journal of Operational Research, 2006, pp. 174, 1553-1566.
 J. Wang, 1999. "Fuzzy outranking approach to prioritize design requirements in quality function deployment," International Journal of Production Research, 1999, pp. 899-916.
 L. V. Vangeas, A. W. Labib, "A fuzzy quality function deployment (FQFD) model for deriving optimum targets," International Journal of Production Research, 2001, pp. 39 , 99-120.
 L. A. Zadeh, 1978 "Fuzzy sets as a basis for a theory of possibility," Fuzzy Sets and Systems, 1978, vol. 1, pp. 3-28.
 J. Drewniak, "Fuzzy Relation Calculus," Univ. Slaski, Katowice, 1989.
 L. A. Zadeh , fuzzy sets , "inform and control," 1965, vol. 8, pp. 338- 353
 V. Nov├ík, I. Perfilieva, J. Mo─ìkoř, "Mathematical principles of fuzzy logic Dodrecht," 1999, Kluwer Academic
 J.G. Klir, S. T. Clair, H. Ute, B. O. Yuan, "Fuzzy set theory: foundations and applications. Englewood Cliffs," NJ: Prentice Hall, 1997.
 X. Zhang, J. Bode, S. Ren, "Neural networks in quality function deployment," Computers and Industrial Engineering, 1996, Vol. 31 (3- 4), pp. 669-673.
 Jia. Lin. Chen, J. Y. Chang, "Fuzzy Perceptron Neural Networks for Classifiers with Numerical Data and Linguistic Rules as Inputs" IEEE Transactions on fuzzy systems, December 2000, Vol. 8, NO. 6.
 J. Chen and S. Lin, "An interactive neural network-based approach for solving multiple criteria decision-making problems," Decision Support Systems, Oct. 2003, vol. 36, no. 2, pp. 137-146.