abj247 / turning_ann_ga

The repo contains the prediction and optimization of Turning parameters of dry conventional lathe for Aluminum 6061-T6 using Artificial Neural Network (ANN) and Genetic Algorithm (GA)

Turning_ANN_GA

This repo conatins the prediction and optimization of Dry turning operation on lathe machine for Aluminum-6061. Artificial Neural Network is used for the prediction of turning parametrs which include Material Removal Rate(MRR) and Surface Roughness (Ra). MATLAB is used for the implementation of neural network using nntool box. The neural network takes 3 inuputs viz. Cutting Velocity(Vc), Depth of cut(D) and feed rate(f). Optimization of Material Removal Rate and Surface Roughness is done using Genetic Algorithm from optimtool present in MATLAB. Minitab is used for the implementation of fitness function for both Material Removal Rate and Surface Roughness. !

R values for training, test and validation sets.

Genetic Algorithm plots