In modern manufacturing, the demand for energy-efficient and material-saving processes has driven advancements in foundry technologies. Lost wax investment casting, known for its ability to produce near-net-shape components with minimal machining, has become a critical method in industries requiring high precision, such as aerospace and fluid control systems. This study focuses on optimizing the lost wax investment casting process for a 304 stainless steel ball valve, which is widely used in high-pressure fluid transmission systems. Traditional casting methods, reliant on empirical parameters, often result in defects like shrinkage porosity and cold shuts at critical regions, such as the junctions between the valve body and flanges. These defects compromise the structural integrity and pressure resistance of the valve, leading to high rejection rates. To address this, we integrate computational simulations with process redesign to minimize defects and enhance production efficiency.
The ball valve component, with overall dimensions of 186 mm × 186 mm × 120 mm and an average flange thickness of 12.5 mm, is manufactured using 304 stainless steel. The chemical composition of the material is detailed in Table 1. Traditional lost wax investment casting processes for this valve involve a step-gating system, which, as observed in initial simulations, leads to significant shrinkage defects. These defects primarily occur due to non-uniform cooling and inadequate feeding in thick sections, such as the valve body-flange junctions. The maximum shrinkage porosity rate in traditional setups reaches 13.2%, as shown in simulation results, with concentrated voids forming in areas distant from the feeding channels. This underscores the necessity for a systematic approach to optimize both the gating system and process parameters.
| C | Cr | Mn | Mo | Ni | S | Si |
|---|---|---|---|---|---|---|
| 0.08 | 18 | 1.5 | 0.5 | 8 | 0.03 | 1 |
To analyze the defect formation, we employed ProCAST software for numerical simulation. The model was meshed with a global element size of 4, generating 116,162 surface elements and 666,312 volume elements after adding a 6 mm ceramic shell. The interfacial heat transfer coefficient between the stainless steel and zircon sand shell was set to 500 W/(m²·K), calculated using the COINC model based on the equation:
$$ Q = \text{Flux} + h(T – T_\alpha) + \sigma \epsilon (T^4 – T_\alpha^4) $$
where \( Q \) is the interfacial heat transfer coefficient, \( \text{Flux} \) is the heat flux, \( h \) is the convective heat transfer coefficient, \( T \) is the surface temperature of the casting, \( T_\alpha \) is the ambient temperature, \( \sigma \) is the Stefan-Boltzmann constant, and \( \epsilon \) is the emissivity. The initial process parameters included a pouring temperature of 1550°C, a pouring speed of 1.5 kg/s, and a shell preheat temperature of 1150°C. Simulation results revealed that shrinkage defects were concentrated at the corners of the valve body and flanges, as these areas experienced delayed solidification and insufficient liquid metal feeding. The high thermal gradient in these regions, combined with the geometry-driven heat dissipation, exacerbated the formation of voids.
In lost wax investment casting, the design of the gating system plays a pivotal role in controlling defect formation. The original step-gating system was replaced with a top-gating configuration featuring two symmetrical ingates at the flange ends. This redesign ensures uniform filling and promotes directional solidification, reducing the risk of isolated liquid pockets. The gating system components include a sprue (length: 100 mm, diameter: 24 mm), a cross-section area ratio of 1.4 times the total ingate area, and a buffer placed 30 mm from the ingates to minimize turbulence. The ingates, with a扇形 (fan-shaped) cross-section and a length of 12 mm, facilitate easy cutting and efficient metal flow. The modified gating system, as modeled in SolidWorks and simulated in ProCAST, resulted in a significant reduction in shrinkage porosity, with the maximum rate dropping to 3.75%. The solidification sequence showed a more progressive pattern, eliminating isolated liquid zones and improving feeding efficiency.
Despite the improvements, residual shrinkage persisted, necessitating further optimization of process parameters. We designed an L9(3^3) orthogonal experiment to evaluate the effects of pouring temperature (A), pouring speed (B), and shell preheat temperature (C) on shrinkage porosity. The factors and levels are summarized in Table 2, and the experimental results are presented in Table 3. The objective was to minimize the maximum shrinkage porosity rate, with each factor tested at three levels to identify optimal conditions.
| Level | A: Pouring Temperature (°C) | B: Pouring Speed (kg/s) | C: Shell Preheat Temperature (°C) |
|---|---|---|---|
| 1 | 1520 | 1.0 | 1120 |
| 2 | 1550 | 1.5 | 1150 |
| 3 | 1580 | 2.0 | 1180 |
| Experiment No. | A (°C) | B (kg/s) | C (°C) | Max Shrinkage Porosity (%) |
|---|---|---|---|---|
| 1 | 1520 | 1.0 | 1120 | 3.10 |
| 2 | 1520 | 1.5 | 1150 | 3.88 |
| 3 | 1520 | 2.0 | 1180 | 3.74 |
| 4 | 1550 | 1.0 | 1150 | 2.29 |
| 5 | 1550 | 1.5 | 1180 | 3.52 |
| 6 | 1550 | 2.0 | 1120 | 4.51 |
| 7 | 1580 | 1.0 | 1180 | 2.44 |
| 8 | 1580 | 1.5 | 1120 | 4.27 |
| 9 | 1580 | 2.0 | 1150 | 3.93 |
The range analysis and variance analysis were performed to determine the influence of each factor. The mean values for each level are calculated as follows: for factor A, the means are \( \bar{A_1} = 3.573 \), \( \bar{A_2} = 3.440 \), and \( \bar{A_3} = 3.547 \); for factor B, \( \bar{B_1} = 2.610 \), \( \bar{B_2} = 3.890 \), and \( \bar{B_3} = 4.060 \); for factor C, \( \bar{C_1} = 3.960 \), \( \bar{C_2} = 3.367 \), and \( \bar{C_3} = 3.233 \). The ranges are \( R_A = 0.133 \), \( R_B = 1.450 \), and \( R_C = 0.727 \), indicating that pouring speed (B) has the most significant effect on shrinkage porosity, followed by shell preheat temperature (C), and pouring temperature (A). The optimal combination is identified as A2B1C2, corresponding to a pouring temperature of 1550°C, pouring speed of 1.0 kg/s, and shell preheat temperature of 1150°C.
Variance analysis further confirms these findings, as shown in Table 4. The F-values for factors B and C are substantially higher than for A, emphasizing their dominance in defect control. The sum of squares for error is minimal, validating the reliability of the experiment. The optimized process parameters, when applied in simulation, reduce the maximum shrinkage porosity to 2.29%, a significant improvement over the traditional method. The solidification behavior under these conditions shows a more uniform temperature distribution, which can be modeled using the Fourier heat conduction equation:
$$ \frac{\partial T}{\partial t} = \alpha \nabla^2 T $$
where \( \alpha \) is the thermal diffusivity, and \( T \) is temperature. This equation helps in predicting the thermal gradients during solidification, ensuring that the casting solidifies directionally from the thin sections to the thick sections, thereby minimizing shrinkage.
| Factor | Sum of Squares | Degrees of Freedom | Mean Square | F-value |
|---|---|---|---|---|
| A: Pouring Temperature | 0.0104 | 2 | 0.0052 | 13.96 |
| B: Pouring Speed | 1.0637 | 2 | 0.5319 | 119.30 |
| C: Shell Preheat Temperature | 0.3422 | 2 | 0.1711 | 38.41 |
| Error | 0.0356 | 2 | 0.0178 | – |
| Total | 1.4519 | 8 | – | – |
Validation through actual production confirms the effectiveness of the optimized lost wax investment casting process. The ball valve castings produced under the A2B1C2 parameters exhibit no visible shrinkage defects at the valve body-flange junctions, with improved surface quality and mechanical integrity. The success of this approach highlights the importance of integrating simulation-driven design with statistical optimization in lost wax investment casting. Furthermore, the reduction in rejection rates contributes to material savings and cost efficiency, aligning with global sustainability goals. The methodology developed here can be extended to other complex components in lost wax investment casting, ensuring high-quality outputs in demanding applications.
In conclusion, the optimization of the lost wax investment casting process for 304 stainless steel ball valves demonstrates the critical role of gating system design and parameter adjustment. Through ProCAST simulations and orthogonal experiments, we identified that a pouring speed of 1.0 kg/s, combined with a pouring temperature of 1550°C and shell preheat temperature of 1150°C, effectively eliminates shrinkage porosity. This study underscores the potential of computational tools in enhancing traditional foundry practices, paving the way for more reliable and efficient manufacturing processes in lost wax investment casting.