Thermal and surface analysis of copper–CNT and copper–graphene-based composite using Taguchi–Grey relational analysis

Abstract

ABSTRACT In this research study, carbon nanotube (CNT) and graphene-reinforced copper composites were fabricated by stir casting process. CNT and graphene were individually infused into copper by 3 and 2 g, respectively. The addition of these nanomaterials enhanced the hardness value of the samples by more than 40% when compared with that of pure copper. Taguchi design of experiments was envisaged to identify the most effective use of the process parameters using a L9 orthogonal array table. Grey relational analysis was used to find the multi-objective optimised range of values for input parameters to minimise surface roughness and contact surface temperature. Furthermore, the depth of cut was found out to be the most influencing factor in the machining process. Regression analysis was used to correlate the relationship among performance variables and compare with pure copper and CNT-based copper composite. Scanning Electron Microscope (SEM) images portrayed a lot of crystal grains in its formed microstructure. It indicates that the forces of cohesion between molecules are weak and the carbon nanomaterial will have less hardness than pure copper.