Influence of hybrid nanofluid on tool wear and surface roughness in MQL-assisted face milling of AISI 52100

Abstract

ABSTRACT With escalating demand for machinability, economical production, health, and environment-related aspects are pushing the present industrial units to drop the usage of harmful-cutting fluid in machining. However, the adaption of this approach for machining difficult-to-cut materials does not ensure favourable outcomes of the tool performance, surface qualities, etc., as friction and heat seriously disturb machining efficiency. This study is focused on near-dry machining employing recently developed hybrid nanofluids-based lubrication in the machining of AISI 52,100 steel. Hexagonal boron nitride (hBN) and silicon carbide (SiC) nanoparticles are added to the lubrication oil to enhance the performance of the Minimum Quantity Lubrication (MQL) system. Taguchi’s method-based Grey relational analysis (GRA) is used for the concurrent optimisation of the tool flank wear and surface roughness. The best parametric setting for the multi-response is achieved as: a lubricant flow rate of 150 ml/h, depth of cut of 0.2 mm, and nanofluid with 0.8 wt % of hBN and 0.2 wt % of SiC nanoparticles. The confirmation experimentation concluded that the multi-response factor is enhanced by 2.48% at the optimum setting with the mean values of TFW and SR as 84 and 0.36 µm, respectively.