Computational investigation of testing parameter effects on abrasive wear behaviour of AL_2O_3 particle-reinforced MMCS using statistical analysis

摘要

The wear rate model of 7.3 vol.% Al_2O_3 particle-reinforced aluminium alloy composites with 16 and 66 μm particle sizes fabricated by molten metal mixing method was developed in terms of applied load, particle size of reinforcement, abrasive grain size and sliding distance based on the Taguchi method. The two-body abrasive wear behaviour of the specimens was investigated using a pin-on-disc abrasion test apparatus where the sample slid against different SiC abrasives under the loads of 2 and 5 N at the room conditions. The orthogonal array, signal-to-noise ratio and analysis of variance were employed to find out the optimal testing parameters. The test results showed that particle size of reinforcement was found to be the most effective factor among the other control parameters on abrasive wear, followed by abrasive grain size. Moreover, the optimal combination of the testing parameters was determined and predicted. The predicted wear rate results were compared with experimental results and found to be quite reliable.