The present work is focused on optimization of machining characteristics of Al/SiCp composites. The machining characteristics such as specific energy, tool wear and surface roughness were studied. The parameters such as volume fraction of SiC, cutting speed and feed rate were considered. Artificial neural networks (ANN) were used to train and simulate the experimental data. Genetic algorithms (GA) was interfaced with ANN to optimize the machining conditions for the desired machining characteristics. Validation of optimized results was also performed by confirmation experiments.
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