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A model of HoQ templet automatic generation based on RBF-ANN
Zhao-Hui Ren   Bing-Cheng Wang   Bang-Chu Wen  
Sch. of Mech. Eng. & Autom., Northeastern Univ., Shenyang, China;

This paper appears in: Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Publication Date: 26-29 Aug. 2004
Volume: 6,  On page(s): 3497- 3500 vol.6
ISSN:
ISBN: 0-7803-8403-2
INSPEC Accession Number: 8244882
Current Version Published: 2005-01-24

Abstract
Quality function deployment (QFD) is a well-known customer-driven methodology of new dryer product development. QFD using house of quality (HoQ) translates customer requirements into all stages of product development. In order to deal with the problems of Dryer conventional quality function deployment (QFD) by employing artificial intelligence theory in QFD, a new concept of intelligent QFD (IQFD) is introduced in this paper. As the key technology of IQFD, the technology of HoQ templet automatic generation is studied, and we propose a model of HoQ templet automatic generation based on the radius basis function artificial neural network (RBF-ANN). An illustrated example shows that the proposed model can map customer requirements into relative engineering characteristics automatically with the support of the knowledge debase and data debase, the difficulty of application of Dryer QFD is decreased, the dependence on experience and knowledge of deign team is reduced.

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