| Author: | Ran, Jiaqi |
| Title: | Inner undercut feature recognition and automatic generation of side actions and inside pins for an injection mold system |
| Degree: | M.Sc. |
| Year: | 2008 |
| Subject: | Hong Kong Polytechnic University -- Dissertations. Injection molding of plastics. Injection molding of plastics -- Methodology. |
| Department: | Department of Mechanical Engineering |
| Pages: | x, 132 leaves : col. ill. ; 30 cm. |
| Language: | English |
| Abstract: | Undercut features are usually molded by side cores and inside pins. These local molding tools must withdraw before the main core and cavity blocks opened along parting direction. The design of side cores and inside pins is done manually at present as the automatic recognition of undercut features and generation of side actions are quite difficult. This thesis provides a new methodology to deal with the automatic design of inside pins via the automatic recognition of undercut features. The outer edge loop which represents the largest boundary projection on a reference plane perpendicular to the given parting direction is first extracted and patched. By classifying the geometrical entities into different types based on their geometrical relationship, the parting surfaces and molding surfaces can be easily identified. After judging whether the bounding boxes of any two inside pins and main core projection have intersection area, deep inner undercut detection result is then generated and the corresponding redesign suggestion is provided. The above - proposed methodology was implemented through case studies, and its advantages in handling complex parts are illustrated compare to previous research. The methodology is proved better than previous work according to computation result and will be developed in the future. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b22328725.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 7.99 MB | Adobe PDF | View/Open |
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