Application of artificial neural network in Al₂O₃ ceramics laser milling

In order to control the quality of Al2O3 ceramics, based on the artificial neural network (ANN), a model was established to describe the relation between the laser milling quality of Al2O3 ceramics with the ceramics parameters. The milling quality of Al2O3 ceramics were predicted with the model in which the input parameters consisted of laser power, scanning speed and defocus amount and the output parameters included the milling depth and width. The results show that the mean error is small, and the model has good verifying precision and excellent ability of predicting. Five group process parameters were chosen to test the reliability of the neural network model out of the train samples. The maximum relative error of the output test value and the experiment sample value was 7.06%. The laser process parameters can be chosen easily and accurately to improve the processing quality of Al2O3 ceramics.