In injection molding simulation the phase change from melt to solid state is usually simplified by using a so called transition temperature. In the present work, the transition temperatures of several amorphous and semicrystalline polymers were determined using DSCruns at different cooling rates. The transition temperature was described as a function of cooling rate. The obtained transition temperatures of the semicrystalline polymers were used in injection molding simulations with the commercial software package Autodesk Moldflow Insight 2010 to calculate the shrinkage and warpage of box-shaped test parts. The simulation results were compared with the experimental values of optically measured injection-molded boxes. The results showed a strong influence of the transition temperatures on the simulation results of a 3D model and a very low influence for a 2.5D model. Transition temperatures obtained at higher cooling rates improved the 3D simulation results for several dimensions.
In this work, a model is presented, which is the basis of a quality control concept for the injection molding process. Contrary to statistical methods, this model uses physical dependencies of two quality parameters on four influencing parameters. The influences of holding pressure, holding time, melt temperature, and mold temperature on part mass and dimensions are described based on the fundamental material behavior such as pvT-data or energy equation. Furthermore, the influence of viscosity changes is indirectly taken into account using the injection work. Assuming only small deviations of the influencing parameters around an optimized operating point, the four parameters are treated as being independent from each other. With this assumption, a product ansatz was chosen with different functions for each influencing factor. Applying basic algebra, the starting equation was transformed into a form that describes either the change in part mass or characteristic part dimensions as a function of the influencing factors. The final equation for the part mass contains six model parameters, whereas nine model parameters are necessary for the equation for the part length. To obtain those model parameters some systematic experiments are required. Once the parameters are known, the model is able to calculate the change of the target values when the influencing factors vary around the operating point. The model was tested experimentally with focus on dimensions using a plastic cover made of an acrylonitrile butadiene styrene (ABS) grade. For the investigated part geometry and material grade, the process behavior was described well by the model. V C 2011Wiley Periodicals, Inc. J Appl Polym Sci 124: [4926][4927][4928][4929][4930][4931][4932][4933][4934] 2012
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