A study on development of a new algorithm for predicting the process variables in GMA welding processes

Gas Metal Arc (GMA) welding is extensively employed in the metal industries to weld a variety of ferrous and non-ferrous metals because of its potenti al for increasing the productivity and quality of welding which is controll ed by the process parameters. The objective of this paper is to develop the algorithm that enables the determination of process variables from the opt imized bead geometry for robotic GMA welding. It depends on the inversion o f empirical equations derived from multiple regression analysis of the rela tionships between the process variables and the bead dimensions using the l east square method. The method directly determines those variables which wi ll give the desired set of bead geometry. This avoids the need to iterate w ith a succession of guesses employed Finite Element Method (FEM). These res ults suggest that process variable from experimental equation for robotic G MA welding may be employed to monitor and control the bead geometry in real time.