Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials
碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 99 === Epoxy resin is current material for LED packaging process. The curing link (gel time) for epoxy resin is a crucial phenomenon, impact the fluidity and yield of modeling process. A survey of literature reveals that formed voids after the Molding Compound curi...
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ndltd-TW-099TIT051170502019-05-15T20:42:29Z http://ndltd.ncl.edu.tw/handle/32z388 Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials 利用樹脂黏度模型進行LED封裝製程參數設計 Kuo-Dung Liao 廖國棟 碩士 國立臺北科技大學 工業工程與管理研究所 99 Epoxy resin is current material for LED packaging process. The curing link (gel time) for epoxy resin is a crucial phenomenon, impact the fluidity and yield of modeling process. A survey of literature reveals that formed voids after the Molding Compound curing. In view of this, electronics manufacturers were not haven viscosity function to determine the process parameters of now product. The viscosity function is recommend in this research could provide prediction accurately. In practice, the phenomenon of process and material variation cause uncertainty of quality. The implement be used in this work include that computer-aided parametric design for experiment of viscosity function, artificial neural networks and location optimizing algorithms (CAFE) for gain the optimum process parametric. At the last, the confirmation experiment is used to proof that parametric recommendatory SN ration increased to 43.7% and 43.8%. 黃乾怡 2011 學位論文 ; thesis 73 zh-TW |
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碩士 === 國立臺北科技大學 === 工業工程與管理研究所 === 99 === Epoxy resin is current material for LED packaging process. The curing link (gel time) for epoxy resin is a crucial phenomenon, impact the fluidity and yield of modeling process. A survey of literature reveals that formed voids after the Molding Compound curing. In view of this, electronics manufacturers were not haven viscosity function to determine the process parameters of now product. The viscosity function is recommend in this research could provide prediction accurately.
In practice, the phenomenon of process and material variation cause uncertainty of quality. The implement be used in this work include that computer-aided parametric design for experiment of viscosity function, artificial neural networks and location optimizing algorithms (CAFE) for gain the optimum process parametric. At the last, the confirmation experiment is used to proof that parametric recommendatory SN ration increased to 43.7% and 43.8%.
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黃乾怡 |
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黃乾怡 Kuo-Dung Liao 廖國棟 |
author |
Kuo-Dung Liao 廖國棟 |
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Kuo-Dung Liao 廖國棟 Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials |
author_sort |
Kuo-Dung Liao |
title |
Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials |
title_short |
Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials |
title_full |
Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials |
title_fullStr |
Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials |
title_full_unstemmed |
Parametric Design for the LED Encapsulation Process Using Viscosity Modeling of Epoxy Materials |
title_sort |
parametric design for the led encapsulation process using viscosity modeling of epoxy materials |
publishDate |
2011 |
url |
http://ndltd.ncl.edu.tw/handle/32z388 |
work_keys_str_mv |
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1719103481086738432 |