Genetic Algorithm Based Optimization of the Process Parameters for Manual Metal Arc Welding of Dissimilar Metal Joint

A better quality weld in dissimilar metal welding is obtained by optimizing the process parameters because they play a vital role in deciding the weld strength. Dissimilar metal joint is extensively used in industries for boilers, economizers and pressure vessels. In this research paper influence of process parameters on manual metal arc welded joint on weld strength and weld deposition rate is discuss. The independently controllable process parameters affecting the weld strength and weld deposition rate these process parameters are welding current (I), welding speed, root gap, electrode angle (A). Experimental run are decided by using Response surface Method. Genetic algorithm (GA)-based technique is successfully developed to model, simulate, and optimize the welding process parameters for maximum weld strength and minimum weld deposition rate.