The investment casting process is renowned for its ability to produce components with excellent surface finish, dimensional accuracy, and complex geometries. However, the inherent complexity of certain casting parts presents significant challenges in preventing internal defects such as shrinkage porosity and cavities. These defects are particularly detrimental in high-stress applications where structural integrity is paramount. This article details a comprehensive investigation and optimization of the investment casting process for a crucial casting part: a mining flatbed truck wheel. Utilizing a combination of numerical simulation and structured experimental design, this study systematically addresses defect formation and establishes an optimized set of process parameters to ensure the production of sound castings.
The subject of this study is a large, disk-shaped wheel used in heavy-duty mining equipment. The casting part is characterized by its significant diameter-to-height ratio and a complex structure featuring a hub, a rim, a connecting web, and several evenly spaced straight slots. As illustrated below, the geometry includes substantial variations in wall thickness, which naturally leads to the formation of thermal hot spots—areas prone to last solidification and subsequent shrinkage defects. Ensuring the soundness of this casting part is critical for its performance under the severe loading conditions of a mining environment.
The material specified for this component is ZG35CrMnSi alloy steel, chosen for its high strength, impact resistance, and wear characteristics. The chemical composition of this alloy is a primary determinant of its solidification behavior and must be carefully considered in the simulation and analysis phases. The chemical composition is summarized in the table below.
| Element | C | Si | Mn | Cr | P | S | Ni | Cu | Mo | V |
|---|---|---|---|---|---|---|---|---|---|---|
| Content (wt.%) | 0.40 | 0.75 | 1.20 | 0.80 | 0.03 | 0.03 | 0.30 | 0.25 | 0.15 | 0.05 |
The initial phase of the work involved the fundamental design of the casting process. The primary objective was to establish a solidification sequence that promotes directional solidification towards the feeding system. For this disk-shaped casting part, a bottom-gating (side-pouring) system was selected. This orientation minimizes the flow distance of the molten metal and positions the gates at the thicker sections of the wheel, facilitating effective feeding. A cluster design for four castings was adopted to improve production efficiency. The gating system was designed using established hydraulic principles. The minimum choke cross-sectional area, which governs the filling time, was calculated using the well-known Osborne Reynolds formula:
$$
F_{min} = \frac{G}{\rho \tau \mu \sqrt{2g H_p}}
$$
where \( F_{min} \) is the minimum cross-sectional area (cm²), \( G \) is the total mass of metal (kg), \( \rho \) is the molten metal density (kg/m³), \( \tau \) is the filling time (s), \( \mu \) is the flow coefficient, \( g \) is gravitational acceleration, and \( H_p \) is the effective metal pressure head (m). Based on the calculated range and standard practices for steel castings, a cross-sectional area ratio for the gating system was established.
With the initial process design established, a full three-dimensional model of the wheel casting part and its gating system was created and analyzed using a dedicated numerical simulation software (e.g., ProCAST). The material properties of ZG35CrMnSi, including its fraction solid curve, density, and thermal conductivity as functions of temperature, were critical inputs for an accurate simulation. The liquidus and solidus temperatures were identified as 1,479 °C and 1,111 °C, respectively. The initial process parameters were set based on standard practices: a pouring temperature of 1,580 °C, a filling speed of 280 mm/s (calculated using empirical formulas), a shell preheat temperature of 1,000 °C, and a zircon-based shell material.
The simulation of the initial process scheme provided valuable insights. The filling sequence was smooth, without excessive turbulence or splashing. However, the solidification analysis revealed the critical issue. The thermal analysis clearly showed that while thinner sections like the web and upper rim solidified first, isolated hot spots remained at the junction between the wheel rim and the base, as well as near the gates. These areas were the last to solidify, leading to inadequate feeding. The direct result, predicted by the shrinkage porosity module, was a significant concentration of shrinkage defects at the bottom of the wheel rim, with a calculated shrinkage porosity percentage of 13.13%. This confirmed that the initial design was insufficient for producing a sound casting part.
To address this shortcoming, the gating system was strategically modified. The core improvement involved adding two new ingates at the bottom of the wheel casting part, effectively increasing the number of feeding points from two to four. This modification aimed to shorten the feeding distance to the critical hot spot at the rim base and provide a more uniform thermal distribution. Additionally, strategic venting was incorporated into the pattern cluster to aid in the escape of gases during pouring. A new simulation of this improved design was run. The results were promising: the predicted shrinkage porosity percentage dropped substantially to 8.65%. The defects at the rim base were markedly reduced, validating the design change. However, minor porosity was still predicted in areas around the web and the wheel base, indicating that further refinement was possible through process parameter optimization.
While the geometry of the gating system is crucial, the final quality of the casting part is equally dependent on several key thermal and kinetic parameters. To systematically find the optimal combination, a Design of Experiments (DOE) approach was employed. Three critical parameters were selected as factors: Pouring Temperature (A), Pouring Speed (B), and Shell Preheat Temperature (C). Each factor was assigned three levels based on practical foundry ranges and prior calculations. The objective function, or response variable, was the simulated shrinkage porosity percentage, which we aimed to minimize. The factors and their levels are defined in the table below.
| Level | A: Pouring Temp. (°C) | B: Pouring Speed (mm/s) | C: Shell Preheat (°C) |
|---|---|---|---|
| 1 | 1,530 | 270 | 750 |
| 2 | 1,555 | 280 | 900 |
| 3 | 1,580 | 290 | 1,000 |
An L9 (3^4) orthogonal array was chosen for the experimental design, requiring only 9 simulation runs to evaluate the effects of the three factors. The improved gating system geometry was held constant for all runs. Each of the 9 combinations was simulated, and the resulting shrinkage porosity percentage was recorded. The experimental layout and results are presented in the following table.
| Run No. | A: Pouring Temp. | B: Pouring Speed | C: Shell Preheat | Shrinkage Porosity (%) |
|---|---|---|---|---|
| 1 | 1 (1,530°C) | 1 (270 mm/s) | 1 (750°C) | 3.10 |
| 2 | 1 | 2 (280 mm/s) | 2 (900°C) | 3.00 |
| 3 | 1 | 3 (290 mm/s) | 3 (1,000°C) | 2.97 |
| 4 | 2 (1,555°C) | 1 | 2 | 3.03 |
| 5 | 2 | 2 | 3 | 3.08 |
| 6 | 2 | 3 | 1 | 3.13 |
| 7 | 3 (1,580°C) | 1 | 3 | 3.04 |
| 8 | 3 | 2 | 2 | 3.08 |
| 9 | 3 | 3 | 1 | 3.30 |
Analysis of the results immediately identifies the best and worst-performing combinations within the test array. Run #3 (A1, B3, C3) yielded the lowest shrinkage porosity at 2.97%, while Run #9 (A3, B3, C1) produced the highest at 3.30%. To determine the statistical significance and the relative influence of each factor, an Analysis of Variance (ANOVA) was performed on the data. The results of the ANOVA are summarized below.
| Variance Source | Sum of Squares | Degrees of Freedom | Mean Square | F-Value | p-Value |
|---|---|---|---|---|---|
| A: Pouring Temp. | 0.036 | 2 | 0.018 | 32.86 | 0.030* |
| B: Pouring Speed | 0.019 | 2 | 0.010 | 17.26 | 0.055 |
| C: Shell Preheat | 0.058 | 2 | 0.029 | 52.23 | 0.019* |
| Error | 0.001 | 2 | 0.001 |
The ANOVA table reveals that both Pouring Temperature (Factor A) and Shell Preheat Temperature (Factor C) have a statistically significant effect on the shrinkage porosity (p-values < 0.05). The effect of Pouring Speed (Factor B) is less pronounced and not statistically significant within the tested range. The F-values indicate the relative strength of each factor’s influence. Based on this analysis, the order of significance for the factors affecting the quality of this specific casting part is: Shell Preheat Temperature (C) > Pouring Temperature (A) > Pouring Speed (B).
Since the goal is to minimize the response (shrinkage porosity), the optimal level for each factor is determined by examining the average response at each level. The level that produces the lowest average shrinkage is chosen. The analysis confirms that the optimal combination derived from the orthogonal test is A1B3C3: a Pouring Temperature of 1,530 °C, a Pouring Speed of 290 mm/s, and a Shell Preheat Temperature of 1,000 °C. A final simulation using this optimal parameter set with the improved gating geometry was conducted. The result showed a near-elimination of shrinkage defects within the critical sections of the wheel casting part, with any residual porosity confined to the feeder system itself, which is later removed during machining. This represents the definitive optimized process for manufacturing this component.
The final and most critical step was the physical validation of the optimized process. The wheel casting part was produced in a foundry setting using the finalized parameters: the modified gating system with four bottom ingates and the optimal parameters of 1,530 °C pouring temperature, 290 mm/s pouring speed, and 1,000 °C shell preheat. The resulting castings were examined and found to be sound, with excellent surface quality and no internal defects detectable by standard non-destructive testing methods in the critical areas. This successful production run confirmed the accuracy and effectiveness of the simulation-driven optimization methodology.
In conclusion, this study demonstrates a robust methodology for solving complex casting defects. For the mining wheel casting part, the initial high defect rate was systematically addressed through a two-stage approach. First, the gating system was redesigned to improve feeding efficiency to the identified thermal hot spots. Second, key thermal process parameters were optimized using a structured orthogonal experiment analyzed via ANOVA. The findings highlighted that for this specific geometry and material, the shell preheat temperature was the most influential parameter, followed by the pouring temperature, with pouring speed having a lesser effect within the tested window. The final optimized process parameters—a lower pouring temperature of 1,530 °C combined with a high shell preheat of 1,000 °C and a slightly increased pouring speed of 290 mm/s—ensured directional solidification and effective feeding, thereby guaranteeing the production of a high-integrity casting part. This integrated approach of simulation and statistical design of experiments significantly reduces the traditional trial-and-error cycle, enhancing both the quality and the development efficiency for complex investment castings.