標題: Optimizing the Auto-brazing Process Quality via a Taguchi-Neural Network Approach in the Automotive Industry
作者: Lin, H. L.
Chou, C. P.
機械工程學系
Department of Mechanical Engineering
關鍵字: Taguchi method;neural network;brazing
公開日期: 2009
摘要: Many parameters affect the quality of the auto-brazing process. It is not easy to obtain optimal parameters of this process. This paper applies an integrated approach using the Taguchi method and a neural network (NN) to optimize the lap joint quality of air conditioner parts. The proposed approach consists of two phases. First phase executes initial optimization via Taguchi method to construct a database for the NN. In second phase, we use a NN with the Levenberg-Marquardt back-propagation (LMBP) algorithm to provide the nonlinear relationship between factors and the response based on the experimental data. Then, a well-trained network model is applied to obtain the optimal factor settings. The experimental results showed that the tensile strength of specimens of the optimal parameters via the proposed approach is better than apply Taguchi method only.
URI: http://dx.doi.org/10.1109/IEEM.2009.5373032
http://hdl.handle.net/11536/134931
ISBN: 978-1-4244-4869-2
ISSN: 2157-3611
DOI: 10.1109/IEEM.2009.5373032
期刊: 2009 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-4
起始頁: 1347
結束頁: +
Appears in Collections:Conferences Paper