Optimization of semi-solid metal processing of A356 aluminum alloy

Abstract

Semi-solid metal (SSM) processing has been recognized as an advanced process to produce high-quality and low-cost engineering components. The cooling slope method is a simple route that can develop non-dendritic slurry for various purposes with reduced equipment and processing costs. In this study, the cooling slope method was employed to produce the A356 feedstock in SSM processing. The dendritic primary phase in the conventionally cast A356 alloy has transformed into a non-dendritic one through the use of ingots cast over a cooling plate with a different pouring temperature. After pouring, the melt that becomes semi-solid at the end of the plate is consequently poured into cylindrical steel molds with different mold temperatures. Also, the process has been conducted in different cooling slopes and different cooling lengths. Then, a back-propagation neural network has been designed to correlate the process parameters to grain size. Finally, genetic algorithm (GA) has been used to optimize the process parameters. Results indicate that the pouring temperature, mold temperature, cooling slope, and cooling length have significant effects on size and morphology of α-Al phase. The GA can optimize the process as well.