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.<\/p>\r\n","references":"[1] S. P. Bingulac, \"On the compatibility of adaptive controllers (Published\r\nConference Proceedings style),\" in Proc. 4th Annu. Allerton Conf.\r\nCircuits and Systems Theory, New York, 1994, pp. 8-16.\r\n[2] G. R. Faulhaber, \"Design of service systems with priority reservation,\"\r\nin Conf. Rec. 1995 IEEE Int. Conf. Communications, pp. 3-8.\r\n[3] W. D. Doyle, \"Magnetization reversal in films with biaxial anisotropy,\"\r\nin 1987 Proc. INTERMAG Conf., pp. 2.2-1-2.2-6.\r\n[4] Arash Shahin, 2005, \"Quality Function Deployment: A Comprehensive\r\nReview,\" 2005.\r\n[5] Richard Zultner, \"Quality Function Deployment (QFD) for software,\"\r\nAmerican Programmer, 1992.\r\n[6] L .K . Chan, M .L .Wu, 2002. \"Quality function deployment: A literature\r\nreview,\" European Journal of Operational Research ,2002 ,pp. 143.\r\n[7] K .J. Kim, H. Moskowitz, A. Dhingra, G. Evans, \"Fuzzy multicriteria\r\nmodels for quality function deployment,\" European Journal of\r\nOperational Research, 2002, pp. 121, 504-518.\r\n[8] H. Liu, F .Kong, \"A new fuzzy MADM method : fuzzy RBF neural\r\nnetwork model,\" LECTURE IN COMPUTER SCIENCE, 2006.\r\n[9] F. Kong, H. Liu, \"fuzzy RBF neural network model for multiple\r\nattribute decision making, \" Lecture Notes in Computer Science, 2006.\r\n[10] J. B. Yang, Y. M. Wang, D. L. XU, \"the evidential reasoning approach\r\nfor MADA under both probabilistic and fuzzy uncertainties,\" European\r\nJournal of Operational Research, 2006, pp. 171(1).\r\n[11] Mr. Mehregan, H. Safari, \"Combination of fuzzy TOPSIS and fuzzy\r\nranking for multiattribute decision making,\" Lecture Notes in Computer\r\nScience, 2006.\r\n[12] \"Rating technical attributes in fuzzy QFD by integrating fuzzy weighted\r\naverage method and fuzzy expected value operator,\" European Journal\r\nof Operational Research, 2006, pp. 174, 1553-1566.\r\n[13] J. Wang, 1999. \"Fuzzy outranking approach to prioritize design\r\nrequirements in quality function deployment,\" International Journal of\r\nProduction Research, 1999, pp. 899-916.\r\n[14] L. V. Vangeas, A. W. Labib, \"A fuzzy quality function deployment\r\n(FQFD) model for deriving optimum targets,\" International Journal of\r\nProduction Research, 2001, pp. 39 , 99-120.\r\n[15] L. A. Zadeh, 1978 \"Fuzzy sets as a basis for a theory of possibility,\"\r\nFuzzy Sets and Systems, 1978, vol. 1, pp. 3-28.\r\n[16] J. Drewniak, \"Fuzzy Relation Calculus,\" Univ. Slaski, Katowice, 1989.\r\n[17] L. A. Zadeh , fuzzy sets , \"inform and control,\" 1965, vol. 8, pp. 338-\r\n353\r\n[18] V. Nov\u251c\u00edk, I. Perfilieva, J. Mo\u2500\u00ecko\u0159, \"Mathematical principles of fuzzy\r\nlogic Dodrecht,\" 1999, Kluwer Academic\r\n[19] J.G. Klir, S. T. Clair, H. Ute, B. O. Yuan, \"Fuzzy set theory: foundations\r\nand applications. Englewood Cliffs,\" NJ: Prentice Hall, 1997.\r\n[20] X. Zhang, J. Bode, S. Ren, \"Neural networks in quality function\r\ndeployment,\" Computers and Industrial Engineering, 1996, Vol. 31 (3-\r\n4), pp. 669-673.\r\n[21] Jia. Lin. Chen, J. Y. Chang, \"Fuzzy Perceptron Neural Networks for\r\nClassifiers with Numerical Data and Linguistic Rules as Inputs\" IEEE\r\nTransactions on fuzzy systems, December 2000, Vol. 8, NO. 6.\r\n[22] J. Chen and S. Lin, \"An interactive neural network-based approach for\r\nsolving multiple criteria decision-making problems,\" Decision Support\r\nSystems, Oct. 2003, vol. 36, no. 2, pp. 137-146.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 52, 2011"}