In the rapidly evolving landscape of new energy vehicles, the demand for lightweight components has intensified. Aluminum alloys, prized for their excellent mechanical properties and low density, are increasingly adopted in automotive applications. As a key player in this transition, our team at an automotive manufacturing facility embarked on the trial production of a critical electronic control housing. This component is slated to be a flagship product for future new energy models, with substantial projected capacity requirements. Ensuring rapid scale-up and quality compliance was paramount for our factory’s strategic shift toward electrification.
During the initial trial phase, we encountered a significant quality issue: the presence of casting holes—specifically, gas and shrinkage pores—on a machined surface of the housing. According to product specifications, no pore defects exceeding φ0.5 mm in diameter are permitted on machined surfaces. However, the scrap rate due to such casting holes initially surpassed 9%, accounting for 52% of total scrap. This defect not only escalated quality costs and delayed deliveries but also burdened machining operations with increased workload and difficulty. Thus, addressing these casting holes became a critical priority.
To systematically tackle this problem, we employed Six Sigma methodologies, focusing on the Define, Measure, Analyze, Improve, and Control (DMAIC) framework. The primary objective was to reduce the scrap rate attributable to casting holes on the machined surface. We began by mapping the process flow and conducting a detailed cause-and-effect analysis using a fishbone diagram. Potential factors influencing the formation of casting holes were identified, including blowing time, spraying time, vacuum position, velocity-pressure (V-P) switch point, machining allowance, cooling structure, and casting pressure.
The process flow for high-pressure die casting of the electronic control housing involves several key stages: die preparation, alloy melting, ladling, injection, solidification, ejection, and trimming. Each stage was scrutinized for variables that could contribute to casting holes. The fishbone diagram categorized these factors into methods, materials, machinery, manpower, and environment. However, for brevity, we focus on the technical parameters analyzed.
We conducted a series of experiments to screen and validate these factors. Statistical analysis, primarily using chi-square tests, was performed to determine the correlation between each factor and the occurrence of casting holes. The null hypothesis for each test was that the factor had no effect on defect formation. A p-value less than 0.05 indicated a significant correlation.
First, blowing time was examined. Insufficient blowing might leave moisture in die gaps, which could vaporize during injection and form gas pores. We adjusted blowing time from the standard 20-30 seconds and sampled parts for defect inspection. The results are summarized in Table 1.
| Blowing Time (s) | Sample Size | Defective Parts | Defect Rate (%) | P-value |
|---|---|---|---|---|
| 20 | 100 | 9 | 9.0 | 0.9227 |
| 25 | 100 | 8 | 8.0 | |
| 30 | 100 | 10 | 10.0 |
The chi-square test yielded a p-value of 0.9227, exceeding 0.05, indicating no significant correlation between blowing time and casting holes. Hence, this factor was eliminated from further consideration.
Next, spraying time was analyzed. Spraying controls die temperature and lubricant application. The initial setting was 20 seconds, with measured die temperature around 160°C. We increased spraying time to 30 seconds and monitored die temperature and defect rates, as shown in Table 2.
| Spraying Time (s) | Die Temperature (°C) | Sample Size | Defective Parts | Defect Rate (%) | P-value |
|---|---|---|---|---|---|
| 20 | 160 | 100 | 9 | 9.0 | 0.754 |
| 30 | 150 | 100 | 8 | 8.0 |
The p-value of 0.754 suggests no significant relationship. Thus, spraying time was not a critical factor for casting holes.
Vacuum position was then investigated. Vacuum extraction reduces air entrapment during high-speed filling, which can lead to gas pores. We adjusted the vacuum port location and collected data, as in Table 3.
| Vacuum Position | Sample Size | Defective Parts | Defect Rate (%) | P-value |
|---|---|---|---|---|
| Original | 100 | 9 | 9.0 | 0.997 |
| Modified | 100 | 9 | 9.0 |
With a p-value of 0.997, vacuum position showed no correlation with casting holes.
The V-P switch point was evaluated next. An early switch might cause incomplete filling, while a late switch could impair pressure transmission during solidification. Adjustments were made, and results are in Table 4.
| V-P Switch Point (mm) | Sample Size | Defective Parts | Defect Rate (%) | P-value |
|---|---|---|---|---|
| 500 | 100 | 9 | 9.0 | 0.816 |
| 550 | 100 | 8 | 8.0 | |
| 600 | 100 | 10 | 10.0 |
The p-value of 0.816 indicates no significant effect on casting holes.
Casting pressure was analyzed. Higher pressure promotes denser microstructure, potentially reducing porosity. We varied casting pressure and observed defect rates, as in Table 5.
| Casting Pressure (MPa) | Sample Size | Defective Parts | Defect Rate (%) | P-value |
|---|---|---|---|---|
| 80 | 100 | 9 | 9.0 | 0.537 |
| 90 | 100 | 8 | 8.0 | |
| 100 | 100 | 7 | 7.0 |
The p-value of 0.537 suggests no correlation, ruling out casting pressure as a key factor for casting holes.
Cooling structure emerged as a potential factor. Regions near cooling channels solidify first, potentially concentrating defects like casting holes in hotter areas. Thermographic imaging showed the defect zone was hotter than adjacent cooled regions. We modified the cooling layout and tested, with results in Table 6.
| Cooling Configuration | Sample Size | Defective Parts | Defect Rate (%) | P-value |
|---|---|---|---|---|
| Original | 100 | 9 | 9.0 | 0.047 |
| Optimized | 100 | 4 | 4.0 |
The p-value of 0.047, below 0.05, indicates a significant correlation. Thus, cooling structure is a critical factor influencing casting holes.
Lastly, machining allowance was examined. Excessive allowance creates thicker sections that solidify last, prone to shrinkage pores—a type of casting hole. Computer-aided engineering (CAE) simulation revealed a pronounced last-to-freeze zone at the defect location under the original allowance. We analyzed the wall thickness and allowance, as shown in Figure 1. The initial machining allowance was 3 mm, leading to a local thickness of 8 mm. After benchmarking and consulting standards, we reduced the allowance to 1.5 mm. CAE simulation confirmed a diminished shrinkage tendency, as illustrated in the thermal analysis.
To quantify the effect, we used the Niyama criterion, a predictive metric for shrinkage porosity in castings. The criterion is given by:
$$ G / \sqrt{T} \leq C $$
where \( G \) is the temperature gradient (°C/mm), \( T \) is the cooling rate (°C/s), and \( C \) is a critical constant. For aluminum alloys, \( C \) typically ranges from 0.5 to 1.0. A lower value indicates higher risk of casting holes. In our CAE analysis, the original design yielded \( G / \sqrt{T} = 0.3 \), while the optimized design improved it to 0.8, reducing the propensity for casting holes.
We also modeled heat transfer during solidification. The Fourier heat conduction equation governs temperature distribution:
$$ \frac{\partial T}{\partial t} = \alpha \nabla^2 T $$
where \( T \) is temperature, \( t \) is time, and \( \alpha \) is thermal diffusivity. For the defect zone, solving this with boundary conditions showed that reduced machining allowance lowered the thermal mass, accelerating cooling and minimizing casting holes.
Based on the analysis, we identified two key factors: cooling structure (X31) and machining allowance (X32). These were the primary drivers of casting holes on the machined surface.
For improvement, we first optimized the cooling structure. Instead of removing cooling entirely—which could lead to uncontrolled die temperatures—we added a new circular cooling channel directly beneath the defect area. This enhanced heat extraction, promoting uniform solidification and reducing casting holes. The cooling capacity was calculated using:
$$ Q = \dot{m} c_p \Delta T $$
where \( Q \) is heat removal rate (W), \( \dot{m} \) is coolant mass flow rate (kg/s), \( c_p \) is specific heat (J/kg·°C), and \( \Delta T \) is temperature rise (°C). We designed the channel to achieve \( Q = 500 \, \text{W} \), sufficient to lower local die temperature by 20°C.
Second, we reduced the machining allowance from 3 mm to 1.5 mm, aligning with industry standards. This decreased the effective wall thickness, as per the relation:
$$ t_{\text{eff}} = t_{\text{base}} + \Delta a $$
where \( t_{\text{eff}} \) is effective thickness, \( t_{\text{base}} \) is base wall thickness (5 mm), and \( \Delta a \) is allowance change. The reduction lowered \( t_{\text{eff}} \) from 8 mm to 6.5 mm, mitigating thermal inertia and casting holes.
We implemented these changes and conducted a production verification from March to June 2023. The scrap rate due to casting holes was monitored monthly, as summarized in Table 7.
| Month | Sample Size | Defective Parts | Scrap Rate (%) | Cumulative Improvement |
|---|---|---|---|---|
| March | 1000 | 90 | 9.0 | Baseline |
| April | 1000 | 45 | 4.5 | 50% reduction |
| May | 1000 | 20 | 2.0 | 78% reduction |
| June | 1000 | 4 | 0.4 | 96% reduction |
The scrap rate from casting holes dropped from 9% to 0.4%, achieving our target. This significant reduction in casting holes enhanced product quality, lowered costs, and improved customer satisfaction.
To solidify the gains, we updated die 3D drawings, revised cooling layout work instructions, and documented technical changes. Control charts were established to monitor casting holes in ongoing production. The process capability index (Cpk) for defect rate improved from 0.5 to 1.5, indicating a stable process with minimal casting holes.
In conclusion, this project underscores the importance of proactive design and process optimization in high-pressure die casting. First, during new product development, machining allowances and added material should be carefully reviewed to avoid localized thick sections that foster casting holes. Second, for thick-walled areas, appropriate cooling layouts are crucial to manage solidification and prevent casting holes. The systematic use of Six Sigma tools, coupled with CAE simulation, enabled us to pinpoint and address the root causes of casting holes, ultimately reducing scrap and supporting our transition to新能源 products.
Future work will focus on predictive maintenance of dies and advanced real-time monitoring to further minimize casting holes. We also plan to explore alloy modifications and injection parameter optimizations to enhance resistance to casting holes in other components. The lessons learned here will be disseminated across our organization to prevent recurrence of similar casting holes issues.