Prediction of energy consumption and surface roughness in reaming operation of Al-6061using ANN based models

Reaming operation is a commonly used finishing phase for already drilled hole. Finishing is required because surface roughness of hole plays a significant role towards the functionality of the component. Surface roughness is a critical parameter for fatigue life of the component. Cutting forces are important indicator for power consumption required for cutting task. An artificial neural network (ANN) based surface roughness and power consumption model was established for Al 6061 under reaming operation. Back propagation neural networks were utilized for prediction of surface roughness and power consumption. Reaming test data was used to train and test the ANN network. In this presented study comparative investigation has been performed between the actual experimental values and neural network outputs to achieve good agreement.