High-Speed Machining of Ti–6Al–4V: RSM-GA based Optimization of Surface Roughness and MRR

Abstract

This article offers experimental research into getting the lowest possible roughness on the surface profile of Ti–6Al–4V produced by High-Speed Machining (HSM) in conjunction with the highest feasible material removal rate (MRR). All three machining variables—cutting speed (mm/min), feed rate (mm/min), and depth of cut (μm)—are investigated in this experiment. The combined optimization of Response Surface Methodology (RSM) and Genetic Algorithm (GA) are used to optimize the cutting parameters for a high-speed end milling operation. For the 20 distinct runs that CCD (Central Composite Designs) offers, employing uncoated cemented carbide end mill cutters is a more affordable choice for cutting the alloy Ti–6Al–4V. Machining data are analyzed with Design Expert software and MATLAB, respectively, utilizing RSM and GA. It has been shown that speeding up the cutting speed (105.56–138.86 mm/min) while decreasing the feed rates (25–37 mm/min) improves surface roughness. The minimum achievable surface roughness predicted by GA and RSM are 0.063 μm and 0.093 μm, respectively. This study presents that the desirability of getting the optimum result would reduce sharply (26.39%) by sacrificing the surface roughness for only 0.1 μm. The cutting edge will be ready for machining with optimum machining combination (cutting speeds of 105.56 and 138.86 m/min and feed rates of 25 and 37 mm/min). The findings illustrate that lowering the surface roughness by only 0.1 μm will increase the MRR rapidly (50.83%). A comparative study on the MRR is also conducted within the investigated input parameters range. The morphology of tool wear and the texture of the machined surface are examined using scanning electron microscopy (SEM) pictures.