Published Paper Details:

The purpose of this study is to demonstrate how, despite the machine tool industry's recent exponential growth in production capabilities, machine tools are still being used to their full potential. This restriction arises from the failure to operate the machine tools under ideal conditions. For a very long time, researchers and practical engineers have been interested in the subject of determining the ideal operating parameter levels. Metal matrix composites are being used more frequently as industrial materials, however since the reinforcements are so hard and abrasive, MMC is very challenging to machine. The MMC is machined as the reinforcement particles are broken and dragged out of the matrix, which results in decreased product surface quality, tool flank wear, and higher machining costs. Additionally, early tool failure increases production time and costs by necessitating frequent tool changes. This method has been suggested by Litak as a way to test the effectiveness of the ripping machine and as a way to keep track of the condition of the tools. Investigating the effects of various machining process factors was the paper's main goal in order to improve the quality of the machined products. The use of the Grey relation, Desirability function, Genetic Algorithm, and Fuzzy logic for multi-response optimization were found to be widely employed, according to a thorough assessment of the literature on the optimization of machining parameters. As a result, it was also attempted through this research project, and the aforementioned techniques were assessed in order to achieve the goal of choosing the proper process parameters for drilling the Al-SiC MMCs.