Abstract
Laser cutting and welding is an efficient way to produce Tailor-Welded Blanks (TWBs). A genetic algorithm (GA)-based artificial neural network (ANN) approach is designed for parameter selection of laser cutting and welding to produce TWBs. These parameters include laser power for cutting and welding, speed for cutting and welding, and pressure of assistant gas. Experimental results demonstrate that the proposed parameter selection approach combines the merits of GA and ANN, and solves the problem of local optimum in ANN and low convergence speed in GA. As a result, it tackles the difficulty in parameter selection of laser cutting and welding and paves the way for TWBs’ production.
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Liu, Y., Xu, D., Wang, X., Tan, M., Zhang, Y. (2007). A Genetic Algorithm-Based Artificial Neural Network Approach for Parameter Selection in the Production of Tailor-Welded Blanks. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_140
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DOI: https://doi.org/10.1007/978-3-540-72395-0_140
Publisher Name: Springer, Berlin, Heidelberg
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