Abstract
The machining forces, tool wear relationship of an Al-SiC (MMCs- Metal Matrix Composites) has been studied in this paper using K20 carbide cutting insert and results being discussed with artificial neural network. This paper presents the optimum machining condition of machining Al-SiC (MMC) by considering cutting force, power consumed, heat generated, MRR (Metal Removal Rate) and surface finish. The worn out tool is also analyzed under optical /Scanning microscope and the parameters are correlated with ANN (Artificial Neural Networks) by giving three input parameters and predicting three output parameters by training the network using back propagation neural network. The result provides some useful information.
