Sustainable Drilling of Nano SiC Reinforced Al Matrix Composites Using MQL and Cryogenic Cooling for Achieving the Better Surface Integrity

Metal Matrix Nano Composites (MMNCs) are progressive alternatives of formal metal materials, are presently accomplishing a growing inclination of research and engineering approaches for challenging operations such as aviation, nuclear power, and automotive for the improved mechanical properties and comparatively light in weight. Machining these MMNC leftovers, however, is a stimulating task as an effect of its mechanical heterogeneity, which primes the product of rapid wear of the tool to worsen the integrity of the surface at the point of machining. This article presents cryogenic Machining (CM), Minimum Quantity Lubrication (MQL) and Dry Machining (DM) of Nano SiC reinforced Al matrix composite and its induced surface integrity characteristics such as surface roughness, burr height and microhardness. The drilling experiments are carried out computer numeric control (CNC) machine considering a carbide drill with dia of 10 mm having a contact point of 90(o), 118(o), and 135(o). The Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-Ray Spectroscopy (EDAX), Atomic Force Microscope (AFM), and Vickers microhardness test are used to assess the subsurface deformation and morphology. An evolutionary Non-dominated Sorting Genetic Algorithm - II (NSGA-II) is used for improving the performances such as surface roughness (SR) and burr height (BH) subjected to distinct cooling environments. The results showed that minimal SR and BH are 0.29 mu m and 0.23 mm respectively under 500 rpm, 50 mm/min feed, 90(0)point angle, and 1% wt of Nano SiC and CM shows reduced depth of plastic deformation in the subsurface of machined composites. The FESEM results show that the better surface finish are found on MMNC surface when machined under CM.

Automated summary

This article introduces different machining methods of Nano SiC reinforced Al matrix composite and their impact on surface integrity characteristics, evaluating the surface and subsurface of machined composites using various microscopy analysis methods. The performances are optimized using a Non-dominated Sorting Genetic Algorithm - II (NSGA-II), demonstrating that cryogenic machining can achieve better surface finish.