Optimization of Casting System Structure Based on Genetic Algorithm for A356 Casting Quality Prediction

To improve the casting quality as well as the casting efficiency during the casting process, the effect of the interaction of process parameters and system structural parameters on the shrinkage volume and efficiency of the casting was investigated in this paper by using the response surface method for the simulation prediction of A356 alloy sand casting. The relationship between variables and response (shrinkage volume, solidification time) was established by Box-Behnken Design with pouring temperature (650–710 °C), mold preheating temperature (200–300 °C), width/thickness ratio of cross-section of sprue (1.2–1.5), width/thickness ratio of inner sprue section (2–4) and length/diameter ratio of straight sprue (1.5–2.5) as variables by the response surface method. The results are then optimized, and the optimal solution is selected by the NSGA-II algorithm and TOPSIS method. The results show that the changes in the cavities of the optimized and improved pouring system enhance the flow of the metal fluid and make the filling more complete. The gentle cooling of temperature is conducive to heat dissipation and layer-by-layer sequential solidification, which can effectively eliminate the casting's internal shrinkage loosening and shrinkage holes defects, thus forming a dense casting with good performance. After solving the optimized parameters and improving the pouring system, the solidification time (integrated solidification time) was reduced from 129.24 to 88.10s, and the shrinkage volume was reduced from 9.68 to 4.06 cm3.