Prediction of laser welding quality by computational intelligence approaches

In this investigation was established a model of laser welding quality prediction based on different input parameters. As the quality factors for the laser welding process lap-shear strength and weld-seam width were used. Laser power, welding speed, stand-off distance and clamping pressure were used as input parameters. Experimental test were used to acquire the training data for the computational intelligence methodologies. In this article support vector regression (SVR) was applied. The results from this study could be used as benchmark results in order to improve the laser welding process.