Investigating the correlation between surface roughness and degree of chip segmentation in A7075 aluminum alloy milling across varied cutting speeds

Abstract

This study investigates the intricate relationship between surface roughness (Ra) and the extent of chip segmentation (Gs) during the milling process of A7075 aluminum alloy across a wide range of cutting speeds. The experimental setup involves variations in feed rate (F) from 0.1 to 0.3 (mm/rev), depth of cut (t) from 0.9 to 1.6 mm, and normal cutting speed (V) ranging from 200 to 500 m/min. By rigorously analyzing experimental data, a robust model is developed, elucidating the complex interdependence of cutting parameters (V, F, t) on surface roughness and chip segmentation. Particularly noteworthy is the significance of this relationship in high-speed machining, specifically ranging from 900 to 1200 m/min. Our clarified findings confirm that feed rate (F) and depth of cut (t) have negligible effects on both surface roughness (Ra) and chip segmentation degree (Gs), while cutting speed (V) significantly influences surface roughness (Ra) and the degree of chip segmentation (Gs) in high-speed machining. This influence becomes particularly prominent at higher speeds, as indicated by ANOVA analysis. Cutting speeds ranging from 900 to 1600 m/min exert an 84.9% influence on chip segmentation degree (Gs) and an 85.4% influence on surface roughness (Ra). The derived mathematical model is rigorously validated under standard and high-speed machining conditions, demonstrating a maximum deviation of 8.58% for Ra and 8.4% for Gs at V = 450 m/min. Notably, this deviation reduces to 4.03% for Ra and 1.92% for Gs at a cutting speed of V = 1200 m/min. To enhance the model's applicability, a comprehensive dataset spanning cutting speeds of 250 to 2000 m/min was utilized. The resulting mathematical relationship between Ra and Gs was rigorously validated against experimental data, revealing evenly distributed bias data with a mean deviation of 3.11% for Gs and 3.54% for Ra.