Investigation on the Effect of Nanofluid-MQL Parameters on Surface Roughness During Milling of Hardened 9CrSi Steel

Nanofluid MQL method has been used in the hard milling process to replace conventional milling for overcoming environmental and economical problems. In the cutting process, the selection of nanofluid MQL parameters is of great significance in improving surface roughness. In this study, the milling of hardened 9CrSi steel under different Al2O3 nanofluid MQL parameters including nanoparticle concentration, pressure, and fluid flow was accomplished. A series of experiments were designed by use of the Taguchi method. The signal to noise (S/N) ratio and ANOVA were applied to find the optimal values of nanofluid MQL parameters for minimizing surface roughness. The result shows that nanofluid MQL condition with the nanoparticle concentration of 4 wt%, the pressure of 3 kg/cm2, and the fluid flow of 90 ml/h presents the better surface roughness. Furthermore, the nanoparticle concentration is the most influential parameter on the surface roughness followed by the pressure.