Novel methods for optimizing CNC aluminum alloy machining parameters in polymer mold cavities

Abstract

The examination of the machining of 7075-T6 aluminum alloy polymer mold cavities using Taguchi optimization and analysis of variance is presented in this paper. This study identified the best CNC milling cutting parameters and used a mathematical model to quantify the surface roughness of the machined cavities. The findings showed that while using a flat endmill, the spindle speed multiplied by feed rate contributed 28.01% to surface roughness, and when using a ball endmill, the squared depth of cut contributed 41.27%. Using both flat and ball endmills, the depth of the cut contributed 98.53% to the material removal rate. A refined second-order linear regression model was employed to forecast the endmill-machined surface roughness. The Warp Surf Portable tester measured values that were outside the error range of approximately 0.257% and 2.8%, respectively, for the expected values. Surface roughness has a 99.97% correlation coefficient in the regression model, indicating a very significant link. Additionally, the study improved the cutting parameters for a ball endmill, which were 3005 Rpm, 726.7 mm/min, and 0.43 mm, and for a flat endmill, these were spindle speed (2500 Rpm), feed rate (650 mm/min), and axial cut depth (0.5 mm). The outcomes demonstrated how well the techniques enhanced mold cavity machining and cost estimation using Ra and MRR data. Consequently, these results can be applied to future academic studies and industrial applications.