Optimal Design of Parameters for the Nanofluid/Ultrasonic Atomization Minimal Quantity Lubrication in a Micromilling Process

Abstract

Nanofluid/ultrasonic atomization minimal quantity lubrication (MQL) was used in an SKD11 steel micromilling process with ultrasonic dispersion. The nanofluid atomizer substantially improved nanofluid reunification and delivery to the cutting zone. The micromilling cutting force and temperature were used to calculate the signal-to-noise ratio (S/N). Normalization of the S/N in the gray relational analysis obtained a gray correlation coefficient, which is used in a fuzzy analysis to obtain a multiple performance characteristic indexes (MPCI). The MPCI is maximized by optimizing the process parameters for multiple quality characteristics and then comparing the optimized parameters with those in the MQL system. Experimental results indicate that the nanofluid parameters containing the density of nanofluid, feed rate, and distance of nozzle are the most influential control factors, while 3.617 N and 117.1 °C, respectively, are the best combination of parameters. Different lubricating methods are also compared in terms of effects on micromilling cutting force, micromilling temperature, micromilling tool wear, and surface burr. Experiments show that nanofluid multiwall carbon nanotube/ultrasonic atomization MQL obtained the best results.