Abstract
Investment casting is widely applied in industries such as aerospace and automotive due to its ability to produce complex structures with high dimensional accuracy and good surface roughness. However, traditional investment casting relies heavily on iterative trial-and-error experiments, leading to high costs. In this paper, we propose an optimized pouring system design for support parts based on trial production results and numerical simulation using ProCAST. Three sets of pouring system designs were evaluated, and the optimal design was determined through simulation and verification in actual production.
1. Introduction
Investment casting can produce castings with complex structures, high dimensional accuracy, and good surface roughness, making it widely used in aerospace, automotive, and other fields. Traditional investment casting relies on a large number of iterative trial-and-error experiments, resulting in high development costs. In recent years, finite element software has become a powerful tool for analyzing the mold filling, solidification, and cooling processes, as well as predicting the location and type of internal defects. By using finite element software, designers can predict the types and distribution of internal defects in castings and verify the rationality of pouring schemes, transforming casting process design from the traditional “iterative trial-and-error method” to the “concept verification method”.
2. Methodology
This paper explores a reasonable investment casting process for support parts. Initially, a simple pouring system was used for trial production, and X-ray detection and fluorescence detection were performed to locate and analyze defects. Based on the trial production results, three sets of pouring system designs were proposed, and the numerical simulation software ProCAST was used to simulate and analyze the temperature field and defect distribution of the optimization schemes. The feasible process scheme was determined based on the simulation results.
3. Pouring System Optimization
3.1 Optimization Schemes
Based on the results of the initial trial production, three optimized pouring system designs were proposed, as shown in Table 1.
| Pouring Scheme | Description | Insulation Cotton Thickness | Number of Gates |
|---|---|---|---|
| “Hui”-shaped | Balances sequential solidification from bottom to top with feeding area of ingates | 12mm (gate cup and cross gate), 6mm (inner and side gates) | 9 per side, symmetrical |
| “Ren”-shaped | Focuses on establishing a reasonable temperature gradient | 12mm | 4 per side |
| “Yi”-shaped | Further optimizes temperature gradient | 12mm | 5, cross-arranged on both sides |
3.2 Solidification Process Analysis
The parameters set in ProCAST are as follows: pouring temperature of 1420°C, mold preheating temperature of 980°C, pouring time of 4s, heat transfer coefficient between mold and casting of 300W/(m2·K), heat transfer coefficients between mold with 12mm and 6mm insulation cotton and air of 0.2W/(m2·K) and 1W/(m2·K), respectively, heat transfer coefficient between mold and air under air cooling of 10W/(m2·K), and room temperature of 20°C.
The Fraction solid criterion in ProCAST indicates the solid fraction of each region of the casting at a certain stage, which can be used to judge whether the feeding channel between the casting and the ingate is closed before the casting is completely solidified and the location of initial solidification during the casting process. All three pouring schemes achieve bottom-up solidification. The “Hui”-shaped pouring scheme has a faster overall cooling rate, while the other two schemes have similar cooling rates.
3.3 Defect Analysis
The numerical simulation software ProCAST predicts the distribution of porosity based on the Niyama criterion. The simulation results for each pouring scheme. The threshold value is set to 0.01, meaning areas with a porosity rate greater than 1% are likely to be defective in actual production.
4. Production Verification
To verify the design of the pouring system, small-scale trial production was conducted according to the optimized scheme. The castings had a smooth surface with no defects such as excess or missing material. X-ray inspection showed no shrinkage porosity or other casting defects inside the castings, and the castings were accepted as qualified.
5. Conclusion
This paper proposes three optimized pouring system designs based on the results of support part trial production and uses numerical simulation software ProCAST to simulate and analyze the three pouring system designs. The main conclusions are as follows:
- The finite element software ProCAST can accurately simulate the mold filling and solidification processes of investment casting and determine the types and distribution of defects within the casting.
- Due to the easy clogging of feeding channels in thin-walled, large-area regions of the casting, an independent solid-liquid mixed zone is formed, leading to shrinkage porosity defects at the end of solidification.
- By changing the structure of the pouring system, the feeding capacity of the gating system to the casting can be effectively improved, the solidification sequence of the casting can be improved, and a solidification sequence from the bottom to the top and from the casting to the pouring system can be achieved, thereby improving the quality of the casting.