Multi Objective Optimization of Robotic GMAW Process Parameters using Genetic Algorithm

摘要

In the present paper, Taguchi techniques has been applied for modeling robotic gas metal arc welding process parameters on IS 2062 E250 BR with output response as weldment mechanical properties in terms of Arc voltage, Arc current, Travel speed and Stick out as input processing parameters. The second order mathematical models in terms of process parameters were developed for output response using regression analysis on the basis of experimental results. The adequacy of the developed models on output responses has been validated with analysis of variances (ANOVA). The output responses are conflict in nature. Hence, the problem is formulated as a multi-objective optimization problem. The formulated problem is solved for optimization using an efficient evolutionary algorithm such as genetic algorithm and obtained the Pareto frontier solution. Confirmation experiments were conducted for validation of the results.