Abstract
A welding process that combined plasma arc welding with laser welding was used to make autogenous bead on plate welds on a sheet stock of a carbon steel. A wide range of welding parameters (arc current, laser power, weld speed) was employed. The experimental weld pool shapes were analysed and the data were used to train a neural network to predict weld pool shape as a function of process conditions. The predictions of the neural network model showed excellent agreement with the experimental results, indicating that a neural network model is a viable means for predicting weld pool shape. Using the model, a parametric study was carried out to examine the influence of process conditions on the final weld pool profile.
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