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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/123276


    Title: Study on Machine identification and its effect on the RSM Optimization in Injection Molding
    Authors: Xu, Rui-Ting;Wang, Tsung-Han;Huang*, Chao-Tsai (CT);Chen, Po-Hsuan;Jong, Wen-Ren;Chen, Shia-Chung;Hsu, David;Chang, Rong-Yeu
    Keywords: injection molding;CAE simulation;response surface method (RSM)
    Date: 2022-06-14
    Issue Date: 2023-04-28 17:30:35 (UTC+8)
    Publisher: Society of Petroleum Engineers, Inc.
    Abstract: Different optimization methods or strategies have been proposed and utilized to enhance the quality of injected products for many years. However, what is the machine characteristics to influence the efficiency of the optimization method? It is not fully understood yet. In this study, the injection machine characteristics has been identified using numerical simulation (Moldex3D) based on a round plate system. The response surface method (RSM) was further utilized for both simulation prediction and experimental conduction to discuss the efficiency of the optimization for operation parameters in injection molding. Results showed that before the machine identification and calibration, the quality of injected part can be improved by 75% theoretically. At the same time, the real experimental system demonstrated worse result. However, the difference between simulation and experiment has the same amount no matter the system has been optimized or not through RSM method. Moreover, after the machine identified and calibrated, the difference between simulation prediction and experimental observation has been improved by 71.4%. Also, the accuracy of the RSM optimization in the real experiment has been enhanced by 50% (from -0.06 mm to 0.03 mm). Obviously, it showed that the machine identification for the real capability is very important.
    Relation: SPE Technical Papers ANTEC2022
    Appears in Collections:[化學工程與材料工程學系暨研究所] 期刊論文

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