Multi-objective Optimization of CNC Milling Parameters of 7075 Aluminium Alloy Using Response Surface Methodology

Optimizing the impact of technological parameters during CNC milling remains a highly practical research direction, hence there have been numerous published research works in this area. This article introduces the results of a multi-parameter optimization study when milling aluminum alloy 7075 on a CNC machine using the Response Surface Methodology (RSM). The experiments were conducted based on the Taguchi L18 orthogonal array with machining parameters including coolant condition, spindle speed, feed rate, and depth of cut. The response parameters in these experiments were surface roughness (Ra) and Material Removal Rate (MRR) measurements.The research results showed that regression models developed for Ra and MRR using the RSM method have high coefficient of determination (R-2) values of 97.67% and 99.36%, respectively, indicating that the developed models, coefficient models are significant. The ANOVA analysis results indicate that machining parameters have a direct impact on both Ra and MRR. Ra is affected by various factors including spindle speed, feed rate, coolant, and depth of cut. Among these factors, spindle speed has the highest impact with a percentage of 37.12%, followed by feed rate at 12.56%, coolant at 12.07%, and depth of cut at 10.13%. On the other hand, the material removal rate (MRR) is mostly influenced by feed rate and depth of cut, with percentages of 41.68% and 47.29%, respectively. Multi-objective optimization using RSM showed that under the conditions of coolant on, spindle speed of 5500 rpm, feed rate of 450 mm/min and depth of cut of 0.369 mm, the optimum values of Ra and MRR obtained are 0.159 mu m and 32.019 g/min, respectively.According to the results of the confirmation experiment conducted to determine the optimal values for Ra and MRR, it was found that the deviation did not exceed 5%. This result is completely acceptable in practical production, thereby affirming the accuracy of the RSM method in solving multi-objective optimization problems in the aluminum alloy CNC miling. (c) 2023 Jordan Journal of Mechanical and Industrial Engineering. All rights reserved