CAE technology for injection molding
CAE (Computer-Aided Engineering) technology for injection molding is an advanced technique that uses computer simulation software to numerically simulate the injection molding process. By establishing mathematical models to simulate melt flow, cooling, and pressure holding, it predicts potential defects during the molding process, thereby optimizing mold design and process parameters, reducing mold trial costs, and shortening product development cycles. The core of CAE technology is to transform complex physical processes into computable mathematical equations. These equations are then solved using the finite element method or the finite volume method to determine the distribution of key parameters such as temperature, pressure, and velocity fields, providing a scientific basis for mold design and process optimization. For example, when developing a new mold, CAE simulations can identify problems such as the location of trapped air in the cavity and the distribution of weld marks in advance, allowing modifications to be made before mold manufacture, avoiding repeated adjustments during subsequent mold trials.
The application of CAE technology in the mold design stage can significantly improve the rationality and reliability of mold design. In cavity and runner design, CAE software can simulate the effects of different runner sizes and gate positions on melt filling, helping designers determine the optimal runner layout and number of gates. For example, for large flat products, by comparing the filling effects of multi-point gates and single-point gates through CAE simulation, it can be found that multi-point gates can reduce the melt flow distance, reduce pressure loss, and make filling more uniform. In cooling system design, CAE technology can simulate the temperature distribution under different cooling water channel layouts, optimize the water channel position and diameter, ensure uniform mold temperature, and reduce product warping. For example, for products with thick-walled ribs, CAE simulation can show that the temperature at the ribs is higher, and additional cooling water channels need to be added nearby to speed up heat dissipation and avoid sink marks.
CAE technology plays a vital role in optimizing process parameters. It can identify the optimal process combination by simulating the effects of different injection speeds, pressures, temperatures, and other parameters on the molding process. Traditionally, determining process parameters relies on empirical mold trials, which is time-consuming and labor-intensive. However, CAE technology allows for virtual mold trials on a computer to quickly screen for the optimal parameter range. For example, for products prone to flash, CAE simulations of cavity pressure distribution under different injection pressures can determine the maximum injection pressure that will fill the cavity without flashing. For crystalline plastics, CAE simulations can predict the distribution of crystallinity at different mold temperatures, helping to determine the optimal mold temperature and improve the mechanical properties of the product. Furthermore, CAE technology can simulate the holding pressure process, optimizing the holding pressure and time, and reducing shrinkage and internal stress in the product.
CAE technology can effectively predict and resolve common defects in injection molding, improving product quality. By simulating the melt filling process, the location and strength of weld lines can be predicted. If weld lines are found in stress-bearing areas, these can be corrected by adjusting the gate position or increasing the melt temperature. If simulation results indicate air entrapment, venting slots can be added at these locations. Temperature unevenness detected during simulated cooling can be addressed by optimizing the cooling system. For example, when molding transparent products, CAE simulations can predict the location of silver streaks, analyze whether the cause is melt degradation or air entrapment, and adjust the barrel temperature or injection speed accordingly. CAE technology can also predict product warpage. By analyzing the causes of warpage (such as uneven cooling and fiber orientation), pre-deformation measures or optimized process parameters can be implemented during mold design to reduce warpage.
With the advancement of computer technology, the application of CAE technology in injection molding has continued to deepen, showing a trend toward multi-physics coupling, intelligence, and integration. Multi-physics coupling simulations can simultaneously consider the interactions of multiple physical processes, such as melt flow, heat transfer, crystallization, and stress, improving simulation accuracy. Intelligent CAE software, through the introduction of artificial intelligence algorithms, can automatically optimize process parameters, reducing reliance on manual experience. Integration seamlessly connects CAE technology with software such as CAD and CAM, achieving full digitization of the entire process, from product design to mold manufacturing and process optimization. For example, some advanced CAE software can directly read CAD models, automatically generate meshes, perform simulation analysis, and directly transmit optimization results to CAM systems to guide mold processing. The continuous advancement of CAE technology has provided strong support for efficient and high-quality production in the injection molding industry, making it an indispensable tool in modern injection molding production.
