The Effect Of Nanoparticle Concentration On Mql Performance When Machining Ti-6Al-4V Titanium Alloy

The main purpose of using cutting fluid during machining processes is to reduce the cutting temperature and friction, and to wash away chips from the cutting zone. However, excessive use of conventional cutting fluid negatively influences human health and environment. Therefore, much research has attempted to improve cutting fluid performance with superior tribological and thermal properties, and to reduce the amount of cutting fluid to minimize machining cost and impact on environment. Recently, Minimum Quantity Lubrication (MQL) technique has been widely investigated as a good alternative to flood coolant. Although MQL improves machining results, its removal heat capability still needs to improve. In this paper, in order to enhance the thermal conductive and viscosity of MQL, nanoparticles were dispersed to make nanofluid coolant. Nanofluids have attracted the attention of investigators due to their good high thermal conductivity and ability to remove heat. In this study, the effect of the cutting speed, feed rate, and nanoparticle concentrations on machining titanium Ti-Al6-V4 alloy were investigated by performing ANOVA analysis. The nanofluid coolant was prepared by adding Aluminum Oxide (Al2O3) nanoparticles to base fluid (vegetable oil) at different weight concentrations (0, 2, and 4%wt).

The ANOVA analysis found that the nanoparticle concentrations and feed rate had a significant influence on surface roughness. The tool wear was also observed to be affected by nanoparticle concentration significantly. The nanoparticles concentration had a significant impact on the flank wear as it could improve the thermal conductivity and lubrication properties of the cutting fluid and reduce the coefficient of friction between the tool- workpiece and toolchip. In terms of the effect of nanoparticle concentrations, 4% wt provided better improvements in both surface roughness and tool wear compared to 2% wt concentration and the pure MQL.