Numerical modelling, prediction of Cu–W nano powder composite in dry sliding wear condition using response surface methodology

Abstract

High-energy mechanical milling was used to reduce the size and mix Cu and W powders. Extruded cylindrical preforms with theoretical density of 93% were prepared using a die and punch assembly with the help of sintering in an electric muffle furnace from 750 to 850°C, and subsequently furnace cooled. Scanning Electron Microscope, Transmission Electron Microscope, Particle Size Analyser, X-ray Diffraction and Energy Dispersive Spectrum were used for characterisation. The experiments were conducted by using a dry sliding wear tester at room condition. Response surface methodology five level central composite approach design was used to minimise the number of experimental conditions and develop mathematical models between the key process parameters namely weight percentage of tungsten, sintering temperature, load and sliding distance to predict the abrasive response of specific wear rate and coefficient of friction. Analysis of variance was used to validate the developed model. The developed mathematical model is effectively used to predict the specific wear rate and coefficient of friction at 99% confidence level.