Optimization of Precision Investment Casting Process for Stainless Steel Brackets Using Numerical Simulation and Orthogonal Experimentation

In precision investment casting, the elimination of shrinkage defects in complex thin-walled components remains a critical challenge. This study focuses on optimizing the casting process for a stainless steel bracket used in agricultural machinery through numerical simulation and experimental validation. We employed ProCAST software to analyze filling patterns, solidification behavior, and defect formation mechanisms, subsequently improving both the gating system and process parameters.

1. Component Characteristics and Process Design

The stainless steel bracket (304L grade) features heterogeneous wall thicknesses (average 4 mm) with multiple geometric discontinuities. The casting dimensions (141 mm × 81.8 mm × 60.84 mm) and complex topology create inherent challenges for directional solidification. Key chemical composition ranges include:

Element C Si Mn Cr Ni
Content (%) ≤0.03 ≤1.0 ≤2.0 18-20 8-11

The initial gating system employed a top-feeding design with single sprue and runner. Pouring velocity was determined using the empirical Kalgin equation:

$$v_{\text{pour}} = \frac{h \cdot \delta \cdot T}{1000}$$

where \(v_{\text{pour}}\) represents pouring velocity (cm/s), \(h\) is casting height (cm), \(\delta\) denotes wall thickness (cm), and \(T\) indicates pouring temperature (°C). Calculated parameters yielded:

Parameter Value
Pouring Temperature 1,500°C
Shell Preheat 1,000°C
Filling Velocity 240 mm/s

2. Numerical Simulation and Defect Analysis

Finite element analysis revealed critical solidification issues in the initial design:

Location Shrinkage Porosity (%)
Rectangular Junction (A) 8.2
U-shaped Housing (B) 6.9
Arc Contact Zone (C) 6.4

Thermal analysis demonstrated premature runner solidification (1,042 s complete solidification time), creating isolated hot spots with insufficient feeding. The original shrinkage porosity rate reached 21.45%, primarily concentrated in geometric transitions.

3. Gating System Optimization

Two modified gating configurations were proposed:

Design Modification Shrinkage Reduction
Scheme A Additional secondary runner 61%
Scheme B Secondary runner + vent channels 70%

Scheme B demonstrated superior performance with:

$$v_{\text{optimized}} = 230\ \text{mm/s}$$
$$T_{\text{shell}} = 1,050°C$$
$$T_{\text{pour}} = 1,650°C$$

4. Orthogonal Experimentation for Parameter Optimization

An L9(3³) orthogonal array evaluated three critical parameters:

Factor Level 1 Level 2 Level 3
A: Pouring Temp (°C) 1,530 1,600 1,650
B: Filling Velocity (mm/s) 200 230 250
C: Shell Preheat (°C) 1,000 1,050 1,100

Optimal parameters reduced shrinkage porosity to 1.34% through enhanced thermal management:

$$Q_{\text{shrinkage}} = \alpha \cdot \Delta T \cdot V_{\text{casting}}$$

where \(\alpha\) represents thermal contraction coefficient (11.5×10⁻⁶/°C for 304L), \(\Delta T\) is temperature gradient, and \(V_{\text{casting}}\) denotes casting volume.

5. Industrial Validation

Production trials confirmed:

  • Defect rate reduction from 21.45% to 1.34%
  • Improved dimensional accuracy (IT12 to IT10)
  • Reduced scrap rate (32% → 4.7%)

This systematic approach demonstrates the effectiveness of combining precision investment casting simulation with statistical optimization for complex thin-walled components. The methodology provides a replicable framework for similar applications in automotive and aerospace industries.

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