Investigation on the Machine Calibration Effect on the Optimization through Design of experiments (DOE) in Injection Molding Parts

doi:10.1016/j.polymertesting.2020.106703

淡江大學機構典藏 > 工學院 > 化學工程與材料工程學系暨研究所 > 期刊論文 > Item 987654321/118942

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题名:	Investigation on the Machine Calibration Effect on the Optimization through Design of experiments (DOE) in Injection Molding Parts
作者:	Huang, Chao-Tsai;Xu, Rui-Ting;Chen, Po-Hsuan;Jong, Wen-Ren;Chen, Shia-Chung
关键词:	Injection molding;CAE;design of experiment (DOE);machine calibration
日期:	2020-10
上传时间:	2020-07-20 12:10:30 (UTC+8)
出版者:	Elsevier Ltd
摘要:	Achieving production quality is a key issue faced in injection molding. Before mass production, ensuring good production quality is one of the crucial factors in injection molding. To achieve good quality, CAE technology is beneficial to assist us either to make the process window approach or to integrate with optimization strategies to improve the quality. However, there are still some questions or challenges existed. For example, for general injection molding, the difference between CAE simulation prediction and real experimental observation is very often encountered. But its mechanism of this difference is not fully understood yet. When design of experiments (DOE) procedure is performed using CAE simulation, the optimal parameters obtained from CAE prediction are expected to be forwarded into the real molding trial. However, there is no guarantee to get results with good accuracy based on those optimal parameters. In this study, we have proposed a feasible methodology to uncover the difference and its internal mechanism between CAE simulation prediction and real experimental observation. It also includes the method to reduce that difference by calibrating the machine performance. Specifically, a standard procedure to calibrate the real performance of the injection machine using CAE technology has been constructed. Moreover, to realize the integration of CAE and DOE optimization strategy, the quality difference between the virtual CAE-DOE and the physical DOE optimization has been investigated before doing the machine calibration. The result showed that the difference between the virtual CAE-DOE and the physical DOE is almost same as that of the original injection molding design. However, after the machine calibration, the quality difference between the virtual CAE-DOE and the physical DOE optimization is reduced by 67%. It is noted that the machine calibration effect is quite significant in injection molding process development.
關聯:	Polymer Testing 90, 106703
DOI:	10.1016/j.polymertesting.2020.106703
显示于类别:	[化學工程與材料工程學系暨研究所] 期刊論文

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