Modeling Volume Loss of Heat Treated Al 6061 Composites Using an Artificial Neural Network

In the present study, artificial neural network (ANN) approach was used to predict the volume loss of heat treated Al 6061 metal matrix composites reinforced with 10% SiC particles and 2% graphite particles. Composite was produced using stir casting process. Volume loss of composite was measured during wear testing in a pin on disc apparatus. Microstructure examination at wear surface was investigated by Scanning Electron Microscope (SEM). In Artificial Neural Network (ANN), Multi Layer Perceptron (MLP) architecture with back-propagation neural network that uses gradient descent learning algorithm is utilized. The results clearly revealed that the developed ANN model is reliable and accurate.