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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.

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The use of aluminum with a reinforced coefficient to increase this material compared to aluminum is used in automotive, aircraft and locomotive industries, in this article, while examining the cutting force and erosion of tools on the machining process of composite aluminum in different percentages of SIC, the machining characteristics are investigated. The end milling operation is performed to obtain the minimum cutting force, tool wear with the maximum removal rate using gray relational analysis based on 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. Proper selection of input parameters (spindle speed 1000 rpm, feed 0.03 mm/rev, depth of cut 1 mm and 5% SiC) produces high material removal rate with fine surface, less tool wear and low cutting force.

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This paper deals with drilling of carbon fiber reinforced polymer (CFRP) composite filled with carbon nanotube (CNT) using response surface method (RSM) based utility function. In the drilling of CFRP composites with a hybrid metal base, the additional advance force and pleat height reduce the performance of the composite. Therefore, to improve the performance of the hybrid metal matrix composite, the advancing force and the pleat height of the composite are minimized. Hence, the advancing force and pleat height are the factors considered in the present research and are the main responses that are minimized using the RSM-based utility function. Four important input factors such as drilling speed, feed rate, CNT percentage and drill helix angle are considered to analyze the performance of the drilling process. The results showed that the advance rate is a very influential parameter that affects the advance force and pleat height in hybrid metal matrix composites. During the drilling operation, due to the mutual rubbing of the CNT abrasive particles, it causes extensive surface damage such as holes, cracks, and fibers coming out. The ANOVA results show that the experimental data are well correlated at the 95% confidence interval, and this technique can be very useful and reliable for predicting drilling parameters of CFRP metal matrix composites.