Abstract
The paper describes the optimization of the hot compaction process to simultaneously increase hardness and decrease the wear coefficient of zirconium silicate reinforced BMCs. L9 orthogonal array is chosen for setup the experiment. Examining the influencing parameters is carried out on factors such as pressure, temperature, particle size, and particle content. Grey relation analysis is used to investigate to produce an optimal combination of parameter levels. The transmission electron scanning is used to study the morphology of zirconium silicate. The wear coefficient of the specimen was investigated by using the weight loss method. A scanning electron microscope was carried out to evaluate the wear track surface of the composite. The test results show that the particle size is the most influential hot compaction parameter. The optimal conditions for the hot compacting process are the temperature level at 350 °C, the pressure level at the 400 MPa level, the particle content level at 12 % weight, and the particle size level at 80 µm. In this optimal condition, the prediction GR-Grade value is 0.695. The validation test results showed that the GR-Grade value increased by 0.15, the hardness increased by 25%, and the wear coefficient decreased by 53%. This optimization method with Gray Relational Analysis has proven to be effective in the hot compaction process for improving the tribology behavior of the composites.
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