Abstract
In this manuscript, a novel approach to RSM models using MOGA along with sensitivity analysis was analyzed. To utilize genetic algorithm approach to inspect the result of micro turning route variables cutting speed, feed, and depth of cut on tool wear and surface roughness of titanium alloy gr.2 using cermet insert. Optimum combination of process variables to explain minimization of tool wear and surface roughness generated is found with the help of computational technique. The GA model parameters change the resulting solution which means Sensitivity analysis. In this investigation, how for sensitive solution and decision variables changes in weights on objective function. It proves that the aggregation method solutions are dependent on weight adjustment. In this method the weights are not properly allocated, the model is not possible to offer good solutions. At the same time, the planned Pareto method is not responsive to weigh, further it does not influence the solution outcome of Pareto based MOGA.
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