Analysis of Machining Parameters for Turning of AL-6061 and Optimization

The paper shows and includes targeted supervision of optimizing machining parameters. Material Removal Rate surface roughness being integral to efficacy any workpiece , simulation based modeling helps in failure mitigation.Thepotential ANN-GA mathematical approach for prediction optimization MRR AL 6061 a analysis statistical study has been discussed. computational model between the desired output inputs have configured using Multiple Regression- Genetic Algorithm Artificial Neural Network(ANN) methods. closeness predicted optimized data sets were mapped integrational ANN with GA interpolate optimality. Keywords: Network(ANN)k, Rate(MRR), algorithm(GA), Surface depth cut feedrate Regression analysis, ANOVA