Optimization of AlO nanoparticle concentration and cutting parameters in hard milling under nanofluid MQL environment

Abstract

The high cutting heat and cutting forces are still the big obstacles in hard machining technology, which puts more pressure to find out the alternative solution for these problems. The work content presents an experimental study on the effect of nanoparticle concentration and cutting parameters on surface roughness and cutting force during hard milling under MQL environment using Al 2 O 3 nano-cutting oil. The Box-Behnken experimental designs for response surface methodology was used to evaluate the influence of the input parameters and determine the optimal values. The obtained results show that the nanoparticle concentration, cutting speed, and feed rate all have the great influences on surface roughness R z and resultant cutting force F , so the study of the influence of these parameters on the efficiency of the hard milling process is very significant. The proposed reasonable value ranges will help technicians quickly choose to meet their demands for specific objective functions. Furthermore, the optimal parameter set of nanoparticle concentration of 1.27 wt%, cutting speed V c = 103 m/min, and feed rate f = 0.09 mm/tooth was determined. It revealed that the use of MQL with nano-cutting oils contributed to improve the lubrication and cooling performance in the cutting zone.