Abstract
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.
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Lin, HL., Chou, CP. Modeling and optimization of Nd:YAG laser micro-weld process using Taguchi Method and a neural network. Int J Adv Manuf Technol 37, 513–522 (2008). https://doi.org/10.1007/s00170-007-0982-3
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DOI: https://doi.org/10.1007/s00170-007-0982-3