Abrasive Wear Analysis of Plasma-Sprayed LaCeYSZ Nanocomposite Coatings Using Experimental Design and ANN

Abstract

The abrasive wear characteristics of plasma-sprayed nanostructured yttria-stabilized zirconia (YSZ) coatings on Inconel 718 substrates was evaluated using AFS 50/70-grade silica sand as abrasives. This article depicts the dependence of abrasive wear characteristics of plasma-sprayed nanocomposite LaCeYSZ coatings on abrading distance, keeping the applied load constant. The influence of four operating parameters—that is, load, wheel speed, time, and temperature with four different levels each—on the performance output (i.e., abrasion wear rate) is studied using Taguchi's L16 orthogonal array design and analysis of variance (ANOVA). Out of the four parameters, load has been found to be most significant factor followed, by speed of the abrasive wheel and temperature influencing abrasion. The morphology of the worn-out surface also showed microcutting and small crater formation in the binder matrix caused by the repetitive impacts of abrasive particles. It was observed that coating with nano-LaCeYSZ grains exhibited higher wear resistance compared to conventional YSZ coating and the reason may be attributed to embedded crack-arresting nanozones, which toughen the coating. An artificial neural network (ANN) approach is then implemented taking into account training and test procedures to predict the triboperformance under different operating conditions. This technique helps in saving time and resources for a large number of experimental trials and successfully predicts the wear rate of the coatings both within and beyond the experimental domain.