A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing

碩士 === 國立交通大學 === 工業工程與管理系所 === 96 === Curl is an unfavorable quality attribute in polyimide film (PI) production. In practice, it is hard to reduce the curl issues for PI films because the production process includes a few hundreds of process parameters. This research combined two data mining algor...

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Bibliographic Details
Main Authors:	Jiun-Lin Huang, 黃俊霖
Other Authors:	Muh-Cherng Wu
Format:	Others
Language:	zh-TW
Published:	2008
Online Access:	http://ndltd.ncl.edu.tw/handle/89320333855769873394

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spelling	ndltd-TW-096NCTU50310222015-10-13T13:51:49Z http://ndltd.ncl.edu.tw/handle/89320333855769873394 A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing 應用資料探勘技術控制PI製程之薄膜捲曲 Jiun-Lin Huang 黃俊霖碩士國立交通大學工業工程與管理系所 96 Curl is an unfavorable quality attribute in polyimide film (PI) production. In practice, it is hard to reduce the curl issues for PI films because the production process includes a few hundreds of process parameters. This research combined two data mining algorithms, 1R and C4.5, for identifying the critical process parameters for reducing the curl issues. Three critical process parameters as well as their appropriate ranges of values were identified by the proposed approach. An empirical experiment reveals that the process yield for reducing the PI curl issues could be improved from 43.36% to 85%. Muh-Cherng Wu 巫木誠 2008 學位論文 ; thesis 59 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立交通大學 === 工業工程與管理系所 === 96 === Curl is an unfavorable quality attribute in polyimide film (PI) production. In practice, it is hard to reduce the curl issues for PI films because the production process includes a few hundreds of process parameters. This research combined two data mining algorithms, 1R and C4.5, for identifying the critical process parameters for reducing the curl issues. Three critical process parameters as well as their appropriate ranges of values were identified by the proposed approach. An empirical experiment reveals that the process yield for reducing the PI curl issues could be improved from 43.36% to 85%.
author2	Muh-Cherng Wu
author_facet	Muh-Cherng Wu Jiun-Lin Huang 黃俊霖
author	Jiun-Lin Huang 黃俊霖
spellingShingle	Jiun-Lin Huang 黃俊霖 A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing
author_sort	Jiun-Lin Huang
title	A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing
title_short	A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing
title_full	A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing
title_fullStr	A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing
title_full_unstemmed	A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing
title_sort	data mining approach to the control of curl for polyimide film manufacturing
publishDate	2008
url	http://ndltd.ncl.edu.tw/handle/89320333855769873394
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A Data Mining Approach to the Control of Curl for Polyimide Film Manufacturing

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