This study focuses on enhancing the quality of mining flatbed wheel castings through precision investment casting optimization. The complex geometry of wheel castings often leads to shrinkage porosity defects during solidification. Numerical simulation and orthogonal experiments were conducted to identify optimal process parameters and improve production efficiency.
1. Structural Characteristics and Material Properties
The wheel casting features a disk-shaped structure with significant thickness variations (15-36 mm) and six radial slots. The ZG35CrMnSi alloy composition is critical for achieving required mechanical properties:
| Element | C | Si | Mn | Cr | Mo | Ni | Cu | V | S | P |
|---|---|---|---|---|---|---|---|---|---|---|
| Content (%) | 0.40 | 0.75 | 1.20 | 0.80 | 0.15 | 0.30 | 0.25 | 0.05 | 0.03 | 0.03 |
Thermophysical properties were calculated using numerical simulation software:
$$ \lambda(T) = 28.5 + 0.015T \quad [W/(m·K)] $$
$$ \rho(T) = 7927 – 0.621(T-25) \quad [kg/m^3] $$
where λ represents thermal conductivity and ρ denotes density.
2. Gating System Design for Precision Investment Casting
The side-pouring gating system was designed based on Chvorinov’s rule and Bernoulli’s equation. The critical cross-sectional area was calculated using the Osborne formula:
$$ F_{min} = \frac{G}{\rho \tau \mu \sqrt{2gH_p}} $$
where:
- $F_{min}$ = minimum cross-sectional area (cm²)
- $G$ = total metal mass (kg)
- $\rho$ = molten metal density (kg/m³)
- $\tau$ = filling time (s)
- $\mu$ = flow coefficient (0.4-0.6)
- $H_p$ = effective metallostatic pressure head (m)
3. Process Parameter Optimization
Three key parameters were investigated through orthogonal experiments:
| Level | A: Pouring Temp (°C) | B: Filling Speed (mm/s) | C: Shell Preheat (°C) |
|---|---|---|---|
| 1 | 1530 | 270 | 750 |
| 2 | 1555 | 280 | 900 |
| 3 | 1580 | 290 | 1000 |
The orthogonal array L9(3⁴) test results revealed:
| Test No. | A | B | C | Porosity (%) |
|---|---|---|---|---|
| 1 | 1 | 1 | 1 | 3.10 |
| 2 | 1 | 2 | 2 | 3.00 |
| 3 | 1 | 3 | 3 | 2.97 |
| 4 | 2 | 1 | 2 | 3.03 |
| 5 | 2 | 2 | 3 | 3.08 |
| 6 | 2 | 3 | 1 | 3.13 |
| 7 | 3 | 1 | 3 | 3.04 |
| 8 | 3 | 2 | 2 | 3.08 |
| 9 | 3 | 3 | 1 | 3.30 |
ANOVA analysis demonstrated the parameter significance order: shell preheat temperature > pouring temperature > filling speed. The optimal combination was determined as A1B3C3 (1530°C pouring temperature, 290 mm/s filling speed, 1000°C shell preheat).
4. Solidification Behavior Analysis
The modified Carlberg equation was employed to predict shrinkage formation:
$$ V_{shrinkage} = \beta(V_{casting} + V_{feeder}) – V_{compensation} $$
where:
- β = volumetric shrinkage coefficient (4.2% for ZG35CrMnSi)
- $V_{compensation}$ = effective feeding volume
Numerical simulation revealed critical solidification sequence:
$$ t_{crit} = \frac{(T_p – T_m)^2}{\pi \alpha (dT/dt)^2} $$
where $T_p$ is pouring temperature and $\alpha$ is thermal diffusivity.
5. Industrial Validation
The optimized precision investment casting parameters reduced porosity from 13.13% to 2.97%, achieving dimensional accuracy of CT7 grade and surface roughness Ra 6.3 μm. Production trials confirmed the elimination of shrinkage defects in critical sections while maintaining mechanical properties:
| Property | Value | Standard |
|---|---|---|
| Yield Strength | ≥450 MPa | GB/T 11352 |
| Tensile Strength | ≥650 MPa | GB/T 11352 |
| Impact Energy | ≥25 J | ASTM E23 |
This research demonstrates how precision investment casting optimization can significantly improve the quality of complex mining components while reducing production costs through virtual process development.