DocumentCode :
2313679
Title :
A model of HoQ templet automatic generation based on RBF-ANN
Author :
Ren, Zhao-Hui ; Wang, Bing-Cheng ; Wen, Bang-Chu
Author_Institution :
Sch. of Mech. Eng. & Autom., Northeastern Univ., Shenyang, China
Volume :
6
fYear :
2004
fDate :
26-29 Aug. 2004
Firstpage :
3497
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.
Keywords :
artificial intelligence; customer satisfaction; drying; product development; quality function deployment; radial basis function networks; customer requirements; dryer product development; house of quality; quality function deployment; radius basis function artificial neural network; templet automatic generation; Application software; Artificial intelligence; Artificial neural networks; Automation; Character generation; Costs; Mechanical engineering; Product development; Production; Quality function deployment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
Type :
conf
DOI :
10.1109/ICMLC.2004.1380394
Filename :
1380394
Link To Document :
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