Optimization and modeling of turning process for aluminium - silicon carbide composite using Artificial Neural Network Models

The major work elements of this paper are manufacturing of Metal Matrix Composites (MMC), Machining of MMC and Optimization and modeling of Machining parameters. The cast is produced through permanent moulding process for the mixing ratio of 15% SiC and 85% Al. A Taguchi´s Orthogonal Array (OA) experiment is designed to carry out the machining operation. Four parameters, namely Tool materials, speed, feed and depth of cut are considered as factors. The output parameters are cutting power, cutting force, shear strength, surface finish and Material removal rate. The output responses are combined to have a single objective as multi response performance index (MRPI) and Manufacturer value function (MVF). ANN models are developed for mapping the relationship between parameters with MRPI and MVF. The optimal process parameters are selected based on the output given by the ANN. The results of both functions are compared by using S/N ratio analysis.