Real Time Analysis of Material Removal Rate and Surface Roughness for Turning of Al-6061 using ANN and GA
Keywords:Artificial Neural Network (ANN), Material Removal Rate (MRR), Genetic Algorithm (GA), Surface roughness, Depth of cut, Feed rate, Regression analysis, ANOVA
The paper shows and includes targeted supervision of optimizing machining parameters. Material Removal Rate and surface roughness being integral to machining efficacy of any workpiece, simulation-based modeling helps in failure mitigation. The potential of ANN-GA mathematical approach for prediction and optimization of MRR and surface roughness of AL 6061, an analysis based statistical study has been discussed. The computational model between the desired output and the inputs have been configured using Multiple Regression- Genetic Algorithm and Artificial Neural Network (ANN) methods. The closeness in predicted and optimized data sets were mapped using integrational ANN with GA to interpolate efficacy in optimality.
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Copyright (c) 2022 Abhishek Jha, Baibhav Kumar, Ashok Kumar Madan
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