淡江大學機構典藏:Item 987654321/120349
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    题名: Machine Calibration Effect on the Optimization through Design of experiments (DOE) in Injection Mold
    作者: Xu, Rui-Ting;Huang, Chao-Tsai;Chen, Po-Hsuan;Jong, Wen-Ren;Chang, Rong-Yeu
    日期: 2020-05-05
    上传时间: 2021-03-20 12:11:11 (UTC+8)
    摘要: Quality issue is one of the most important concerns in injection molding. However, before executing mass production, how to retain good quality is one of the crucial factors in injection molding. To retain good quality, it is commonly using CAE to assist from original design to revision and to fabrication. However, even using CAE, it doesn’t guarantee the quality factors obtained from CAE can be applied to real experiments. Moreover, the design of experiment (DOE) method has been utilized into injection molding product development. Today, there are still some challenges when people using DOE in injection molding. In this study, we have designed one injection molding system to define quality factor based on a circle plate. Then, we have tried to perform a series virtual DOE testing for injection molding using CAE to optimize the process condition. Furthermore, we also performed real DOE experiment to verify the virtual DOE concept. Finally, we will discuss about the machine calibration effect on the accuracy of quality comparison. Results shows that before machine calibrated, both virtual CAE-DOE and real DOE optimization can provide better quality for injection parts. However, there is some difference between the virtual and real DOE results. To find out why the difference between the virtual and real DOE results happened, we have investigated the machine feature and tried to calibrate it. After machine calibrated, the difference between the virtual and real DOE results has been improved by 58%.
    關聯: SPE Technical Papers, ANTEC2020-054, p.1-6
    显示于类别:[化學工程與材料工程學系暨研究所] 會議論文

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