Modeling and optimization of Nd:YAG laser micro-weld process using Taguchi Method and a neural network

被引：0
|
作者：
Lin, Hsuan-Liang [1 ]
Chou, Chang-Pin [2 ]
机构：
[1] Department of Vehicle Engineering, Army Academy, R.O.C., 113, Jungshan E. Rd., Jungli, Taoyuan, 320, Taiwan
[2] Department of Mechanical Engineering, National Chiao Tung University, Hsinchu 300, Taiwan
来源：
International Journal of Advanced Manufacturing Technology | 2008年 / 37卷 / 5-6期
关键词：
The use of a pulsed Nd:YAG laser in the 0.1 mm- thick aluminum alloy lap micro-weld process was optimized. The welding parameters that influence the quality of the pulsed Nd:YAG laser lap micro-weld were evaluated by measuring of the tensile-shear strength. In this work; the Taguchi method was adopted to perform the initial optimization of the pulsed Nd:YAG laser micro-weld process parameters. A neural network with a Levenberg-Marquardt back-propagation (LMBP) algorithm was then adopted to develop the relationships between the welding process parameters and the tensile-shear strength of each weldment. The optimal parameters of the pulsed Nd:YAG laser micro-weld process were determined by simulating parameters using a well-trained back-propagation neural network model. Experimental results illustrate the proposed approach. © 2007 Springer-Verlag London Limited;
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页码：513 / 522
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