Simulation studies were performed on filling imbalance in geometrically balanced injection molds. A special simulation procedure was applied to simulate properly the phenomenon, including inertia effects and 3D tetrahedron meshing as well as meshing of the nozzle. The phenomenon was investigated by simulation using several different runner systems at various thermo-rheological material parameters and process operating conditions. It has been observed that the Cross-WLF parameters, index flow, critical shear stress (relaxation time), and zero viscosity, as well as thermal diffusivity and heat transfer coefficient strongly affect the filling imbalance. The effect is substantially dependent on the runners’ layout geometry, as well as on the operating conditions, flow rate, and shear rate. The standard layout geometry and the corrected layout with circled element induce positive imbalance which means that inner cavities fills out faster, and it is opposite for the corrected layouts with one/two overturn elements which cause negative imbalance. Generally, for the standard layout geometry and the corrected layout with circled element, an effect of the zero shear rate viscosity η0 is positive (imbalance increases with an increase of viscosity), and an effect of the power law index n and the relaxation time λ is negative (imbalance decreases with an increase of index n and relaxation time λ). An effect of the thermal diffusivity α and heat transfer coefficient h is negative while an effect of the shear rate is positive. For the corrected layouts with one/two overturn elements, the results of simulations indicate opposite relationships. A novel optimization approach solving the filling imbalance problem and a novel concept of global modeling of injection molding process are also discussed.
Experimental and theoretical studies were performed on filling imbalance in geometrically balanced injection molds. Balancing the melt flow between cavities was investigated using several different runner systems at various operating conditions. Experiments indicate that injection rate, mold, and melt temperatures substantially affect the filling imbalance. It is strongly dependent on runners layouts geometry, and it has never been eliminated completely. It is most difficult to remove for high injection rates and low melt temperatures. Standard element geometry and circled element geometry cause positive imbalance which means that inner cavities fills faster, and it is opposite for one/two overturn element geometries which induce negative imbalance. A special modeling procedure is required to simulate properly the imbalance. This includes inertia effects, geometrical modeling of the nozzle where the imbalance starts, 3D tetrahedron meshing with minimum 12 layers. Simulations were consistent with experiment, however, when the imbalance increased, the discrepancies between simulation and experiment also increased. It can be stated that filling imbalance problem is still unsolved. There are serious thermo‐rheological aspects to explain for better understanding this phenomenon. Trends in modeling of injection molding are presented and new concepts solving the problem are discussed including simulation/optimization approach and a novel concept of global modeling of injection molding process. POLYM. ENG. SCI., 59:233–245, 2019. © 2018 Society of Plastics Engineers
Simulation and experimental studies were performed on filling imbalance in geometrically balanced injection molds. An original strategy for problem solving was developed to optimize the imbalance phenomenon. The phenomenon was studied both by simulation and experimentation using several different runner systems at various thermo-rheological material parameters and process operating conditions. Three optimization procedures were applied, Response Surface Methodology (RSM), Taguchi method, and Artificial Neural Networks (ANN). Operating process parameters: the injection rate, melt temperature, and mold temperature, as well as the geometry of the runner system were optimized. The imbalance of mold filling as well as the process parameters: the injection pressure, injection time, and molding temperature were optimization criteria. It was concluded that all the optimization procedures improved filling imbalance. However, the Artificial Neural Networks approach seems to be the most efficient optimization procedure, and the Brain Construction Algorithm (BSM) is proposed for problem solving of the imbalance phenomenon.
Przeprowadzono badania dooewiadczalne zjawiska nierównomiernego wype³niania wielogniazdowych form wtryskowych zrównowa¿onych geometrycznie, podczas wtryskiwania tworzyw amorficznych i czêoeciowo krystalicznych, z zastosowaniem ró¿nych rozwi¹zañ konstrukcyjnych kana-³ów doprowadzaj¹cych. Wykonano badania symulacyjne wp³ywu warunków wtryskiwania (natê¿enia przep³ywu i temperatury ch³odzenia) na stopieñ nierównomiernooeci wype³nienia formy.
Simulation of injection molding of polymeric materials is still a series scientific and engineering problem. The quality of the input data is crucial for computation accuracy. The original, relatively simple tool has been designed to validate simulations. This allows a fast identification of the critical input data, and next their proper adjustment to computations. FEM simulations have been compared with directly registered pictures of cavity filling process in a special injection mold with a sight-glass.
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