Optimal Selection of Cutting Parameters for Surface Roughness in Milling Machining of AA6061-T6

Abstract

Due to its ability to remove material quickly while maintaining optimum surface quality, end milling is considered one of the most frequent metal cutting procedures in industry. The present study aimed to investigate the impacts of cutting parameters and tool geometry on milling of Aluminum Alloy 6061-T6 to examine the impact surface roughness by utilizing response surface methodology (RSM). RSM was used to create a second-order mathematical model of surface roughness for this purpose. A multiple regression analysis used the analysis of variance to demonstrate the effect of machining settings on surface roughness and determine experiment performance. The trials for optimizing surface roughness were set up utilizing the central composite design (CCD) method and various cutting parameters such as spindle speed, feed rate and depth of cut. Also the parameters used in tool geometry are the radial rake angle (10, 13, 16, 19 and 22 degrees), and nose radius (0, 0.2, 0.4, 0.6 and 0.8 mm). The result shows that the nose radius has more significant effect on the surface roughness followed by the radial rake angle. Moreover, the effect of the depth of cut on surface roughness is more dominant than cutting speed. The optimum combinations of cutting and tool geometry parameters were cutting speed (60.53 m/min), feed rate (0.025 mm/tooth), depth of cut (0.84 mm), radial rake angle (12.72 degree) and nose radius (0.34 mm).

Optimization of vibration amplitude ratio of face mill tool of VMC and analysis with design expert to endorsing shim design

“…Using a CoCo 80 dynamic signal analyzer, vibration signals from physical components are converted into numerical data that can be carefully studied and analyzed (Guo et al, 2021). Vibration signals are recorded with a double cut, under various cutting conditions, and with various shims in order to detect chatter (Fratila and Caizar, 2011;Zhou et al, 2018;Pimenov et al, 2019;Sambedana and Jagadeesha, 2019;Narooei and Ramli, 2022;Ma et al, 2022). EDM and MATLAB tools were used to create TDR (Time Displacement Response) and FFT (Fast Fourier Transformation) graphs.…”