Statistical Modeling and Optimization of MRR And Surface Quality in Milling Aluminum Matrix Composite with Different Percentages of SIC

The use of aluminum with a reinforced coefficient to increase this material compared to aluminum is used in the automotive, aircraft, and locomotive industries. This article examines the parameters of the material removal rate (MRR) rate and surface quality in the machining process of composite aluminum in different percentages of SIC. It examines the machining characteristics of end milling operations to obtain minimum surface quality, cutting force, and chip removal rate with maximum material removal rate using gray relational analysis based on the response surface design method (RSM). Twenty-seven experimental runs were carried out based on the response surface design method (RSM) by changing the parameters of spindle speed, feed, and depth of cut in different weight percentages of reinforcements such as silicon carbide (SiC-5%, 10%, 15%). And alumina (5-5% Al2O3) in the aluminum metal base 7075. Gray relation analysis was used to solve the multi-response optimization problem by changing the weights for different responses based on quality or productivity process requirements. The results show that spindle speed and SiC weight percentage are the most important factors that affect the machining properties of hybrid composites.