Investigation of machining performance of Al2O3 CuO Graphene nanoparticles based coolant in turning operation

Abstract

The primary objective of this thesis is to prepare newlineand examine the optimum dispersion parameters of newlinethree nano coolants that is copper, aluminium and newlinegraphene and optimized the machining parameters for newlinesurface roughness and material removal rate by using newlinethe best concentration of these nano coolants. newlineThe thesis is organized into two modules. newlineThe first module focuses on using Taguchi-based grey newlinerelational analysis to determine the optimal newlinedispersion parameters for three nano coolants: newlinecopper, aluminium, and graphene. The study s newlineobjective is to evaluate the dispersion properties of newlinecopper nanoparticles in distilled water with sodium newlinelauryl sulfate (SLS). A comprehensive approach is newlineused to analyse the optimized dispersion properties newlineof copper nanoparticles as a cutting fluid, newlineconsidering responses such as thermal conductivity, newlinesurface tension, and viscosity. Experimental trials newlineare conducted using Taguchi orthogonal arrays, with newlinenanoparticle mass, surfactant concentration, and newlinesonication time as input parameters. For copper nano newlinecoolant, the optimal parameters identified through newlinegrey relational analysis for maximum thermal newlineconductivity, minimum surface tension, and viscosity newlineare 0.277 grams of nanoparticle mass, 50 minutes of newlinesonication time, and 0.100 grams of surfactant newlineconcentration. For aluminium and graphene nano newlinecoolants, the optimal parameters are 0.277 grams of newlinenanoparticle mass, 30 minutes of sonication time, and newline0.249 grams of surfactant concentration.The study reveals that graphene nano coolant newlineachieves the highest thermal conductivity, measured newlineat 1.48 W/m-K. Key parameters, including thermal newlineconductivity, surface tension, and viscosity, were newlineobtained for all samples of nano coolant and newlinesubsequently used in the S-N models.This research confirms that optimizing newlinedispersion properties enhances thermal conductivity newlinewhile reducing surface tension and viscosity, newlinesupporting the effectiveness of these optimized newlinenanoparticle dispersion properties as a cutting newlinecoolant.