Optimization of abrasive wear performance in aluminium hybrid metal matrix composites using Taguchi–grey relational analysis

Abstract

In this study, the Taguchi–grey relational analysis was used for the optimization of hybrid aluminium composites considering multiple quality characteristics of the material and process parameters relevant to two-body abrasive wear behaviour. Hybrid aluminium composites containing alumina and molybdenum disulphide particulates were produced by stir casting method. Volume loss and frictional force were measured using a pin-on-disc apparatus. In this study, applied load, sliding speed and abrasive size were taken as process parameters and percentage of molybdenum disulphide considered as material parameter. An L9 orthogonal array was used for the Taguchi experimental design. Optimum process parameters were determined using the grey relational analysis for multiple performance characteristics such as wear rate and coefficient of friction. Analysis of variance was used to study the impact of individual factors on the wear rate and coefficient of friction. Experimental results showed that two-body abrasive wear performance of the hybrid composites improved under optimal test conditions. Scanning electron microscopy investigations of the worn out specimens were carried out to explain the wear mechanism of the hybrid composites during two-body abrasive wear.