Optimization of turning process parameters for enhanced surface quality in aluminum alloy AA2024

Surface roughness is a critical parameter that profoundly influences the functionality and performance of materials and components across various industries. Additionally, estimating the ideal machining parameter circumstances is the best way to minimize costs and get the item's surface quality. This research investigated four factors- depth of cut, spindle speed, feed, and nose radius- for the turning of aluminum alloy AA2024 to estimate the surface roughness. The study's experimental efforts were done by utilizing a manual turning machine, and the experiment setup used the Taguchi method of L18 array orthogonal (OA). The Taguchi approach is employed to optimize the selection of tools. The average surface roughness (Ra) measurements were converted to signal-to-noise (S/N) ratios and analyzed statistically using the analysis of variance (ANOVA) method. The results illustrated that nose radius, feed, speed, and depth of cut that produced the best results were 0.8, 0.066 mm/min, 1100 rpm, and 0.9 mm, respectively. The feed rate contributed the most with 54.51%, while the nose radius had the smallest impact with 0.84% of the percentage contribution. A2/B3/C1/D2 is the most efficient arrangement for lathe parameters. Among the selected components, only the feed rate showed a significant P-value of 0.006. Surface roughness offers numerous benefits for AA2024, an aluminum alloy widely utilized in aerospace applications. Enhanced surface roughness fosters better adhesion of coatings and adhesives and is crucial for strong bonds in aircraft components.