PREDICTION OF THE INFLUENCE OF ROLLING PROCESS PARAMETERS ON THE MECHANICAL PROPERTIES OF RARE-EARTH-CONTAINING ALUMINUM ALLOYS

Abstract

This study investigated the effects of rolling temperature and total reduction ratio on the mechanical properties of a rare-earth-containing Al-Mg-Si alloy, aiming to optimize the strength–ductility balance during thermomechanical processing. Rolling experiments were conducted under different temperatures and reduction ratios, and the resulting mechanical properties were evaluated by tensile testing and hardness measurements. Optical microscopy, scanning electron microscopy, and electron backscatter diffraction were employed to characterize microstructural evolution and to clarify the process–microstructure–property relationship. The results showed that increasing the total reduction ratio significantly improved yield strength, ultimate tensile strength, and hardness, but reduced elongation, whereas increasing the rolling temperature weakened the strengthening effect while enhancing ductility. The highest strength was achieved at 25 °C with a 70% reduction ratio, while the best elongation was obtained at 400 °C with a 30% reduction ratio. A favorable strength–ductility balance was realized at 200 °C and 50% reduction. In addition, quadratic regression and random forest models were developed to predict mechanical properties, and the random forest model exhibited higher accuracy. This work establishes a process–microstructure–property framework and highlights machine-learning-assisted prediction as a useful strategy for optimizing rare-earth-containing aluminum alloys.