Abstract
This article presents a feed forward backpropagation neural network model for predicting the turning parameters of Al-Cu/TiB2 in-situ metal matrix composites (MMCs). The workpiece material is prepared by casting route and then extruded as cylindrical rod. The experiments are designed using 33 factorial design and conducted on computer numerical control (CNC) lathe. The input parameters for artificial neural network (ANN) model are cutting speed, feed and depth of cut. The output parameters for the model are tangential and axial forces, surface roughness and material removal rate. The ANN model is trained and tested with a set of input and output parameters. The predicted response values using ANN model are found to be in very good agreement with the untrained experimental values.
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