This paper presents an experimental design approach to the process parameter optimization for Compocasting of A356-SiCp composites. Toward this end, parameters of stirring temperature, stirring time, stirring speed and SiC content were chosen and three levels of these parameters were considered. The D-optimal design of experiment (DODE) was employed for experimental design and analysis of results. In the experimental stage, different 20 μ m-sized SiC particle contents (5, 10 and 15 vol %) were introduced into semisolid-state A356 aluminium alloy. Semisolid stirring was carried out at temperatures of 590, 600 and 610 ° C with stirring speeds of 200, 400 and 600 rpm for 10, 20 and 30 min. The effect of these parameters on the distribution of the SiC particles within the matrix, represented by distribution factor (DF), was investigated. The smaller value of DF is indicative of the more uniform distribution of the SiC particles in the matrix. It was observed that the SiC particle content of 15 vol %, stirring temperature of 590 ° C, stirring speed of 500 rpm, and stirring time of 30 min were the optimum parameter values producing the best distribution of the SiC particles in the matrix. The statistical test revealed that the main effect of the stirring temperature is the most significant factor.

In the conventional casting process, the presence of porosity in the structure is inevitable. Compocasting method is one of the processes for composite production. Performing friction stir processing as a complementary process will modify the microstructure and good distribution of reinforcing particles in the matrix. Therefore, in this study, friction stir processing was used to improve the composite properties of A390 / 10wt% SiC composites. The FSP process was performed at rotational and traveling speeds of 800rpm and 40 mm / min, respectively. Three ratios of shoulder diameter to pin diameter (D/d) of 2, 2. 5 and 3 were used, each of them was processed in one to three passes. An optical microscope (OM) was used to examine the microstructure of the processed samples. Microstructural data and its association with the results of the hardness and tensile test yielded the desired parameter. The results showed that FSP modifies the microstructure including resizing and distribution of SiC particles, primary silicon as well as changes the grain size of aluminum. The uniform distribution of particles on one side and the reduction of the grain size of aluminum, on the other hand, is effective in determining the desired parameter. The highest strength and toughness in the D/d ratio was 2. 5 and in the third pass were 260MPa and 10. 8M J/m3, respectively. Also, the average particle size of SiC, silicon and aluminum grains in the optimum parameter were 2. 98, 14. 98 and 16. 3 μ m, respectively.