Optimization of Deposition Rate in Gas Metal Arc Welding Process using Genetic Algorithm

Gas metal arc welding is a high quality arc welding process used in industry. In this process an electric arc is established between a continuous filler metal and the weld pool being protecting by a shielding gas. Selecting appropriate values for input variables in this welding process is essential in order to control the quality of weldments. In this paper, the deposition rate in gas metal arc welding of ST-37 steel has been optimized by genetic algorithm. In this connection, a five level five factor rotatable central composite design was used to collect the welding data (with -2, -1, 0, +1,+2 levels) and the deposition rate was modeled as a function of wire feed rate, welding voltage, nozzle-to-plate distance, welding speed and gas flow rate by regression analysis. Then the deposition rate as the fitness function was minimized by genetic algorithm. The result shows that in order to obtain the lower deposition rate, wire feed rate ,welding voltage, welding speed ,nozzle-to- plate distance and gas flow rate must be at -2, - 0.824, +2, 0.85 and -2 levels, respectively.

Keywords:

Gas metal arc welding , Deposition rate , Genetic algorithm , Rotatable central composite design