In mold flow analysis, the need to mesh an entire mold set, including all mold plates, is increased recently as it can yield more realistic data for further analysis. However, it requires much more time to process the entire mold in comparison with that using a simplified mold base, because the pre-processing of CAD models is tedious and time consuming. In addition, the human effort required for the entire process would be increased if repeated work must be performed due to improper CAD design. The purpose of this project is to investigate the optimization of feature parameters and simplification of related holes for injection molds in mold flow analysis. The former can investigate the correctness of feature design on the CAD model, whereas the latter can simplify unnecessary holes on the mold set in mold flow analysis; both can enhance the efficiency of mold flow analysis. For the optimization of feature parameters, the rib data obtained from feature recognition must further be classified and screened to characterize the dominant faces that can be used to determine the width, height, thickness and draft angle of a rib. For those parameters that are not satisfied, a design modification module is then implemented to modify the shape of the rib. The above-mentioned method is modified slightly to handle tube and boss features. For the simplification of related holes for a mold set, adjacent and coaxial holes on different mold plates are recognized and grouped, including those from different CAD models. Holes belonging to the core, cavity, sprue and cooling channels are preserved as they must be modeled in mold flow analysis, whereas the others on the mold set are simplified. Finally, the mold sets before and after the above-mentioned CAD pre-processing are meshed to verify the feasibility of the proposed method.
|Effective start/end date||1/08/19 → 31/07/20|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- Feature recognition
- direct modeling
- optimization of feature parameters
- hole recognition
- hole simplification
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