An approach for solving multi characteristics optimization of submerged are welding process parameters by using grey based genetic algorithm

Abstract

The quality of a weld joint is directly influenced by the welding input parameters during welding and the joint quality can be defined in terms of properties like weld-bead geometry, mechanical properties and distortion. In this paper, an attempt has been made to find the optimal process parameters for achieving good quality welded joint by using multi objective function genetic algorithms (GA). Taguchi design of experiment (DOE) was used for conducting the experiment and these experimental data used to develop regression model for correlating mechanical properties with the process parameters. Grey relational analysis has been introduced to convert the multi objective function into single objective one, which will be the objective function in genetic algorithm.