Prediction of Part Shrinkage for Injection Molded Crystalline Polymer via Cavity Pressure and Melt Temperature Monitoring
Source abstract
Abstract
During an injection molding process, different parts of the molded material are subjected to various thermal–mechanical stresses, such as variable pressures, temperatures, and shear stresses. These variations form different pressure–temperature paths on the pressure–volume–temperature diagram. If these paths cannot converge at a specific target volume value during ejection, it often leads to different levels of shrinkage and associated warping, which pose a significant challenge for molders during mold trials and part quality control. The situation is particularly complicated when molding crystalline polymers because the degree of crystallinity depends on the processing conditions and may vary across different locations. In this study, we propose an innovative and practical approach to improving part shrinkage when molding crystalline polymers. For the first time, we utilized melt temperature profile monitoring rather than the previous mold temperature measurement to detect the crystallization process and determine the time taken to complete the crystallization at different melt and mold temperatures. In addition, we used response surface methodology to build a crystallization time prediction model. The feasibility of the prediction model was verified by determining the warpage of parts molded at various cooling times. Based on this model, we varied the packing pressure, packing time, and melt temperatures to determine the correlation with part shrinkage. Through regression analysis, the time-averaged solidification pressure values can accurately control part shrinkage. Two prediction models provide reasonable accuracy and efficiency for part shrinkage control, as demonstrated by subsequent verification experiments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Injection Molding Process and Properties · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
R&D Center for Smart Manufacturing, Chung Yuan Christian University, Taoyuan 32023, Taiwan
R&D Center for Semiconductor Carrier, Chung Yuan Christian University, Taoyuan 32023, Taiwan
Funding
National Science and Technology Council · Smart Manufacturing R&D Centers for Semiconductor Carrier of Chung Yuan Christian University, Taiwan, ROC
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Show source-provided references
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