Prediction and optimisation of abrasive wear model for particle reinforced MMCs using statistical analysis

摘要

In the present study, the wear weight loss model of aluminium alloy composites reinforced withn16 mm Al2O3 particles using varying volume fraction of particles up to 23?3 vol.-% fabricated bynmolten metal mixing method was developed in terms of volume fraction of reinforcement, abrasivengrain size and sliding distance based on the Taguchi method. The two-body abrasive wearnbehaviour of the specimens was investigated using a pin-on-disc abrasion test apparatus againstndifferent SiC abrasives at room temperature. The orthogonal array, signal to noise ratio andnanalysis of variance were employed to find out the optimal testing parameters. The test resultsnshowed that the volume fraction of reinforcement was found to be the most effective factor amongnother control parameters in abrasive wear, followed by sliding distance. However, abrasive grainnsize and sliding distance had a much smaller effect compared to the volume fraction ofnreinforcement. The predicted weight loss of the composites was found to be in good agreementnwith the experimentally observed ones.