Regression model based properties prediction of A356 aluminum alloy rheocast using cooling slope technique

Abstract

The current research work involves experimental research of the Al-alloy rheocasting with enhanced microstructural and mechanical characteristics after using the Semi-Solid Metal (SSM) processing method, which is the cooling slope method. The studies here were carried out online with Central Composite Design (CCD) in order to create a non-linear regression model to represent the fabrication of A356 casting considering the Cooling Slope (CS) Technique. During the rheocasting, the angle as well as the length of the slope, along with nozzle height were taken as the input process parameters, whereas the microhardness, grain size, and sphericity of the sample were treated as the responses. The variation of such responses across the cross-section of the casting was measured at three different locations such as the center, mean, and outer radii. The non-linear regression techniques applied to the A356 sample were manufactured under two circumstances, such as ‘with’ and ‘without’ isothermal treatment. The regression models thus developed were validated by incorporating Analysis of the Variance (ANOVA). Further, the correctness of the regression representations was verified through ten experimental test samples. The percentage deviation of experimental outcomes from the model-predicted outputs was minimal. The developed mathematical models were representative of the physical process with reasonably good accuracy.