Core Technologies of Mold Flow Analysis for Optimizing Injection Mold Defects
In modern injection molding production, product defect rates, material waste, and production halts caused by mold defects are common pain points in the industry. According to industry statistics, the first-time mold trial pass rate of molds without mold flow analysis optimization is only 40%-50%, while common defects directly lead to a production efficiency decrease of over 30%. Based on computational fluid dynamics (CFD) and thermodynamics principles, mold flow analysis can accurately simulate the entire process of plastic melt in the mold cavity, providing a scientific basis for mold design and process adjustment. The spline test mold is a key carrier for verifying analysis results, and the combination of the two forms the core system for defect control.
I. Common Defects of Injection Molds and Their Impact on Production
1. Types of Common Defects
Typical defects in injection mold production include flash, short shot, air bubbles, warpage deformation, weld lines, and sink marks. Among these, the occurrence rate of flash in thin-walled products is as high as 60%; weld lines are common in products with complex cavities; and warpage deformation is prominent in engineering plastic products such as ABS and PC.
2. Impact on Production Efficiency and Product Quality
The rework rate caused by flash is approximately 15%-20%, with an average rework time of 3-5 minutes per piece; material waste caused by short shots accounts for 8%-12%; and the scrap rate of products with warpage deformation can be as high as 25%. In addition, the mold shutdown and debugging time due to defect handling accounts for 20%-25% of the total production time, severely restricting production capacity.
II. Basic Principles and Key Data of Mold Flow Analysis
1. Basic Principle of Mold Flow Analysis
By establishing a 3D mold model and a plastic material database, it simulates the entire process of melt from injection to cooling and solidification. With the help of numerical calculations, it reproduces the distribution of temperature field, pressure field, and velocity field, and predicts the location and cause of defects.
2. Interpretation of Key Data Indicators
Core data indicators include flow time, pressure distribution, temperature distribution, shear rate, and solidification time. The difference in flow time should be controlled within ±0.3s; the maximum injection pressure in the cavity should be less than 85% of the mold's allowable pressure (the allowable pressure of general engineering plastic molds is 150-200MPa); the uniformity error of temperature distribution should be ≤5℃; the shear rate should be controlled between 1000-5000s⁻¹; and the solidification time usually accounts for 70%-80% of the total cooling time.
III. Core Methods of Mold Flow Analysis for Optimizing Injection Mold Defects
1. Optimization of Gate Design
(1) Determination of Gate Position: Based on the simulation of the melt flow path, the gate is set at the farthest point of melt flow in the cavity or the position with the maximum wall thickness, avoiding the key stress-bearing areas of the product. For single-cavity products, the number of gates is usually 1-2.
(2) Optimization of Gate Size: Calculated based on material fluidity and product weight, the gate diameter for small PP products is 0.8-1.2mm, and for large products, it is 1.5-2.5mm.
2. Optimization of Runner System
(1) Runner Layout Design: Priority is given to a balanced layout to ensure consistent melt flow distance and pressure loss in each cavity. The difference in runner length should be controlled within 5%. The diameter of the main runner is 1-2mm larger than that of the sub-runners, and the diameter of the sub-runners is 4-8mm.
(2) Optimization of Runner Size: Ensure that the pressure loss of the melt in the runner is ≤30MPa, and reduce the filling time difference of multi-cavity molds to within 0.2s.
3. Optimization of Cooling System
(1) Cooling Water Channel Design: Follow the principle of "close to the cavity and uniform distribution". The distance between the water channel and the cavity surface is 15-25mm, and the spacing between water channels is 25-35mm. Conformal water channels are used for molds with complex curved surfaces, which can improve cooling uniformity by more than 40%.
(2) Selection of Cooling Medium: Industrial cooling water (temperature 20-25℃) with a flow rate of 1.5-2.5m/s is used for ordinary products; ice water cooling (temperature 5-10℃) is used for engineering plastic or thick-walled products, and the temperature fluctuation of the mold surface is ≤3℃.
4. Optimization of Injection Process Parameters
(1) Injection Pressure and Speed: The injection pressure is set to 1.1-1.2 times the maximum pressure of the cavity. A segmented speed is adopted: 30-50mm/s in the initial filling stage, 60-100mm/s in the middle stage, and 20-40mm/s in the final stage.
(2) Holding Pressure and Time: The holding pressure is 60%-80% of the injection pressure. The holding time is determined by the product wall thickness—for every 1mm increase in wall thickness, the holding time is extended by 1-1.5s.
(3) Molding Temperature: The barrel temperature is 20-40℃ higher than the plastic melting point (200-240℃ for ABS materials, 260-300℃ for PC materials); for mold temperature, it is 40-80℃ for crystalline plastics and 60-120℃ for amorphous plastics.
IV. Application of Spline Test Molds in Mold Flow Analysis
1. Overview of Spline Test Molds
A standard mold specially used to verify mold flow analysis results, adopting the size of ISO 527-2 standard tensile splines (170mm×15mm×4mm). It can be designed with single or multi-cavity, equipped with standard gates, runners, and cooling systems. By producing standard splines, it detects the consistency between material molding performance and analysis data.
2. Key Design Points of Spline Test Molds
The mold core material is preferably S136 or H13 mold steel, with a hardness of HRC50-55 after heat treatment; the surface roughness of the cavity is Ra≤0.8μm; the ejection system uses a combination of ejector pins and ejector plates, with ejector pin diameter of 2-3mm and spacing of 30-40mm; and mounting holes for temperature sensors are reserved to monitor the cavity temperature in real time.
3. Role of Spline Testing in Mold Flow Analysis
It serves as a "calibrator" for analysis results, correcting model parameters by comparing simulated and measured data. For example, if the mold flow analysis predicts a spline warpage of 0.5mm and the actual measurement is 0.52mm, the error can be reduced to within ±3% after adjustment. At the same time, it can verify process parameters in advance—such as testing the weld line strength of splines under different injection speeds to determine the optimal process range.
V. Practical Case Analysis
A company used ABS material to produce automotive door trim strips. The first mold trial showed severe weld lines and warpage deformation, with a defect rate of 12%. Mold flow analysis revealed that the single-gate design of the original mold resulted in an excessively long melt filling path, and uneven distribution of cooling water channels caused an 8℃ temperature difference in the cavity.
Optimization Plan: Add 1 auxiliary gate and adopt a balanced runner; adjust the spacing of cooling water channels to 30mm and add 2 conformal water channels. Spline testing showed that the tensile strength of the spline weld line increased from 18MPa to 25MPa, and the warpage decreased from 0.8mm to 0.3mm.
After applying the optimization plan, the weld line strength of the product met the standard, warpage deformation was controllable, the defect rate dropped to 2.5%, production efficiency increased by 28%, and material waste per batch decreased by 10%.
VI. Development Trends of Mold Flow Analysis Technology
1. Integration with AI and Big Data
Moving towards intelligence, AI algorithms automatically identify design defects and parameter optimization spaces, and combine with big data to realize model self-learning and self-calibration. Some systems can complete the full-process analysis of complex molds within 10 minutes, improving efficiency by more than 50%.
2. Multi-Physical Field Coupling Simulation
Strengthen the coupling analysis of flow field, temperature field, and stress field, simulate the interaction between melt flow and mold structure deformation, and combine with software collaborative simulation to realize full-chain digital verification from design to performance prediction.
VII. Conclusion
Mold flow analysis is the core technology for optimizing injection mold defects, and spline test molds improve the reliability of optimization solutions. By optimizing design and processes, combined with spline test verification, the incidence of defects can be significantly reduced, and the first-time mold trial pass rate can be improved. With the development of technology integration, mold flow analysis will play a greater role in the field of precision injection molding, promoting the industry's transformation towards high efficiency, accuracy, and intelligence. Establishing a closed-loop system of "mold flow analysis - spline testing - mold optimization" is the key for enterprises to enhance their competitiveness.
