Optimization of surface qualities in face milling of EN-31 employing hBN nanoparticles-based minimum quantity lubrication

Abstract

EN-31 steel is used for making moulding dies, bearings, and other automobile parts which are subjected to heavy wear and tear. The main requirements in such applications are the high surface finish and good surface microhardness. However, controlling the machining variables for one of these characteristics doesn’t ensure good results for the other one. Thus, it became essential to execute multi-response optimization to determine the ideal parametric setting for both characteristics. In the current study, the Grey Relational Analysis (GRA) is used for concurrent optimization of surface roughness and surface microhardness while face milling of EN-31 by employing nano-particle-based minimum quantity lubrication (MQL). The nanohBN (Hexagonal Boron Nitride) nanoparticles are mixed in lubricating oil to enhance the lubricating and cooling effects of the MQL system. The ideal parametric combination for the multi-response factor is obtained as a lubricant flow rate of 100 ml/hr, Spraying distance of 40 mm, and hBNnano-particles weight concentration of 1 % in lubricating oil. All MQL variables have shown a significant impact on the multi-response factor. The lubricant flow rate has shown the highest significance for the multi-response factor with a contribution of 58.1 %.