Studies on Machining Parameters While Milling Particle Reinforced Hybrid (Al6061/Al2O3/Gr) MMC

Abstract

In this article, response surface methodology has been used for finding the optimal machining parameters values for cutting force, surface roughness, and tool wear while milling aluminum hybrid composites. In order to perform the experiment, various machining parameters such as feed, cutting speed, depth of cut, and weight (wt) fraction of alumina (Al2O3) were planned based on face-centered, central composite design. Stir casting method is used to fabricate the composites with various wt fractions (5%, 10%, and 15%) of Al2O3. The multiple regression analysis is used to develop mathematical models, and the models are tested using analysis of variance (ANOVA). Evaluation on the effects and interactions of the machining parameters on the cutting force, surface roughness, and tool wear was carried out using ANOVA. The developed models were used for multiple-response optimization by desirability function approach to determine the optimum machining parameters. The optimum machining parameters obtained from the experimental results showed that lower cutting force, surface roughness, and tool wear can be obtained by employing the combination of higher cutting speed, low feed, lower depth of cut, and higher wt fraction of alumina when face milling hybrid composites using polycrystalline diamond insert.