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

機構典藏 > College of Engineering > Graduate Institute & Department of Chemical and Materials Engineering > Journal Article > Item 987654321/118942

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/118942

Title:	Investigation on the Machine Calibration Effect on the Optimization through Design of experiments (DOE) in Injection Molding Parts
Authors:	Huang, Chao-Tsai;Xu, Rui-Ting;Chen, Po-Hsuan;Jong, Wen-Ren;Chen, Shia-Chung
Keywords:	Injection molding;CAE;design of experiment (DOE);machine calibration
Date:	2020-10
Issue Date:	2020-07-20 12:10:30 (UTC+8)
Publisher:	Elsevier Ltd
Abstract:	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.
Relation:	Polymer Testing 90, 106703
DOI:	10.1016/j.polymertesting.2020.106703
Appears in Collections:	[Graduate Institute & Department of Chemical and Materials Engineering] Journal Article

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	122	View/Open

Loading...