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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/5909
Title: A capacitive transducer for process and quality monitoring in injection molding
Authors: Fung, Ka Tsai
Issue Date: 2006
Abstract: On-line monitoring of injection molding is of great importance to process and product quality control. In view of the shortcoming of soft-sensor and the existing hardware-based sensors for process monitoring, a capacitive transducer as an alternative hardware sensor has been developed for in-mold monitoring. Previous study by Gao’s research group has shown that the capacitive transducer has been able to detect in-mold flow velocity and position; the start and end of filling; V/P transfer point; gate freezing time as well as over-packing. In this project, it is further demonstrated that this sensor can on-line predict the in-mold part weight effectively. Experiments under various conditions show that the proposed on-line weight prediction is robust and effective. It paves the way for on-line closed-loop part weight control. The application of the in-mold capacitive transducer is also extended for on-line check-ring failure detection for injection molding. Considering the limitation of the set of mold embedded solely with the capacitive transducer, a completely new set of hot-sprue mold fitted with additional commercial sensors and controlled gating option is specially designed. In that way, the performance of the capacitive transducer for process monitoring is again verified. In addition, the solidification status of the polymer melt and the in-mold part detachment can be potentially monitored by the capacitive transducer. On top of the application in real-time process monitoring, after-molding shrinkage is predicted well based on the capacitive transducer. It can be concluded that the robust capacitive transducer is capable for product quality prediction, fault detection and also real-time monitoring throughout the whole injection cycle.
Description: Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006
xvi, 123 leaves : ill. ; 30 cm
HKUST Call Number: Thesis CENG 2006 FungK
URI: http://hdl.handle.net/1783.1/5909
Appears in Collections:CBME Master Theses

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