Abstract
Laser welding of plastic materials has a wide range of applications in the packaging, medical, electronics and automobile industries provided it can predict high quality welds compared with other joining methods. Laser welding process parameters can affect the quality of welds. In this paper, Artificial Neural Network (ANN) is used to model the effects of laser power, welding speed, clamp pressure and stand-off distance on weld lap-shear strength in laser transmission welding (LTW) of acrylic (polymathy methacrylate). A set of experimental data on diode laser weld lap-shear strengths was used to train and test the ANN from which the neurons relations were gradually extracted to develop a model. The developed ANN model can be used for the analysis and prediction of the complex relationships between the above mentioned process parameters and weld lap-shear strength. The results indicated that increase in laser power and clamp pressure increases the weld lap-shear strength whereas welding speed and stand off distance had a decreasing affect on shear strength at high value.
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