INVESTIGATION INTO THE EFFECT OF THE CUTTING PARAMETERS ON THE BURR HEIGHT IN CO2 LASER NITROGEN CUTTING OF AISI 304 STAINLESS STEEL

The purpose of this study is to develop predictive model for burr height in CO2 laser nitrogen cutting of AISI 304 stainless steel using artificial neural network (ANN). The ANN mathematical model of the burr height was expressed as explicit nonlinear function of the laser cutting parameters such as the laser power, the cutting speed, the assist gas pressure and the focus position. To obtain experimental database for the ANN training, laser cutting experiment was planned as per Taguchi's L-27 orthogonal array. Statistically assessed as adequate, ANN model was then used to investigate the effect of the selected cutting parameters on the burr height. Additionally, 3D surface plots were generated using the ANN model to study the interaction effects of the cutting parameters. The analysis reveals that the focus position has far the most significant effect, while the assist gas pressure has the least effect.