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반복적인 RSM과 RLS를 이용한 LCD 모듈 실장 설비의 모델 추정 및 정도 품질 향상

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dc.contributor.author백상훈-
dc.contributor.author허건수-
dc.date.accessioned2022-07-16T18:07:33Z-
dc.date.available2022-07-16T18:07:33Z-
dc.date.created2021-05-13-
dc.date.issued2011-11-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/167036-
dc.description.abstractRecently mounting technology with high specifications is required for of high-precision LCD TV. In the LCD module manufacturing process, the OLB process includes vision system recognizing the distance between electronic device and LCD pattern, linear motion system adjusting alignment with a backlash, bonding system with high temperature and pressure, and finally, inspection system. The vision system with lens distortion and resolution is modeled as a 3-order polynomial. The motion system model consists of a conditional backlash. The bonding system model contains a few rational expressions with lot-based CTE. Also each model has standard normal distribution noise. Unknown parameters of the models are estimated with input and output data using recursive RSM and RLS. R-square and RMAE are used to measure the accuracy of the estimated parameters. The estimated offset and setting parameters from the reliable model improve mounting accuracy. The trend of estimated parameters helps monitoring and diagnosis of equipment status. This proposed algorithm has been tested with simulation.-
dc.language한국어-
dc.language.isoko-
dc.publisher대한기계학회-
dc.title반복적인 RSM과 RLS를 이용한 LCD 모듈 실장 설비의 모델 추정 및 정도 품질 향상-
dc.title.alternativeModel estimation and quality improvement of fine mounting equipment using RSM and RLS in LCD module process-
dc.typeArticle-
dc.contributor.affiliatedAuthor허건수-
dc.identifier.bibliographicCitation대한기계학회 춘추학술대회, no. , pp. 1117 - 1122-
dc.relation.isPartOf대한기계학회 춘추학술대회-
dc.citation.title대한기계학회 춘추학술대회-
dc.citation.startPage1117-
dc.citation.endPage1122-
dc.type.rimsART-
dc.type.docTypeProceeding-
dc.description.journalClass2-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassother-
dc.subject.keywordAuthorRSM(Response Surface Method-
dc.subject.keywordAuthor반응표면법), RLS(Recursive Least Square-
dc.subject.keywordAuthor반복최소제곱법), Lens Distortion(렌즈 왜곡), Backlash(백래시), Thermal Expansion(열팽창), OLB(Outer Lead Bonding), Model-based estimation(모델기반 추정)-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE02041799-
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서울 공과대학 > 서울 미래자동차공학과 > 1. Journal Articles

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