With the development of the foundry industry in the direction of specialization, intelligence and green, compared with the traditional sand casting, the lost foam casting technology can obtain high-quality, high-precision and high-performance castings, which is praised as “the green revolution of the foundry industry” and “the foundry technology of the 21st century” by the foundry industry at home and abroad. With the extensive application of lost foam casting in the fields of military industry such as thermal power equipment, automobile, aerospace and weapons, higher and higher requirements are put forward for the development cost, casting quality and economic benefits of lost foam casting products.
Many defects in the casting process are closely related to the design optimization of the process. With the continuous development of simulation research of casting process, more and more computer simulation technology is applied in the casting industry. Jiang Mengqi et al. took the gating system design of turbine investment casting as an example, combined the Box-Behnken experimental design and genetic algorithm to obtain a turbine casting with no defects and a process yield of 80.53%. Wang Doufeng et al. used the Anycasting software and the orthogonal test method to optimize the aluminum alloy ignition seat, and analyzed the filling and solidification of the alloy under different conditions, and predicted the location and size of shrinkage porosity and shrinkage cavity.
Gao Haofei and others simulated the mold filling and solidification of valve body parts based on ProCAST software, predicted the possible shrinkage porosity, shrinkage cavity and other defects during the casting process, and optimized the process plan according to the simulation results, thus improving the quality of investment castings. Wang Donghong et al. combined the coupled numerical simulation technology with the response surface analysis method, and used the established second-order response equation to seek the optimal combination of process parameters, realizing the rapid optimization of investment casting simulation. Li Junhong et al. used ProCAST software to simulate the pressure casting process, designed a numerical simulation research scheme with Box-Behnken method, recorded the response of the shrinkage porosity of the gearbox cover, and effectively explored the optimal process parameters to eliminate defects. Dong Changchun et al. used InteCAST software, used three different test methods for the same steel casting, and compared the optimization effects of genetic algorithm, fruit fly algorithm and interior point algorithm. The results of numerical simulation analysis showed that the three algorithms can better improve the quality of castings.
Cai Qing and others used ProCAST software to study the hot cracking behavior of ZL205A in the metal mold casting process, and used the temperature field and stress field models to simulate and predict the hot cracking position of the casting, thus improving the quality of the casting. Liu Shanshan et al. used ProCAST software to study the hot tearing problem of duplex stainless steel produced in continuous casting process. According to the hot tearing index criteria, the influence of operating parameters on the hot tearing sensitivity was analyzed. Zhao Huibin et al. used ProCAST software to compare and analyze the solidification process of castings under different pouring temperatures in vacuum integral precision casting, and predicted the hot cracking based on the simulation results. The results showed that the numerical simulation prediction was consistent with the hot cracking of castings.
ProCAST software was used to simulate the valve body in lost foam casting. The shrinkage porosity and shrinkage defects were eliminated by optimizing the gating system. On this basis, Box-Behnken experimental design was used to optimize the process. Different pouring temperatures, vacuum degrees and pouring speeds were selected for simulation, and the hot cracking tendency of the valve body lost foam casting under different process conditions was analyzed to obtain the optimal combination of process parameters.