Outlier detection in lithography: benchmarking and the creation of a new algorithm
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/100950 |
Resumo: | Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics |
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7160 |
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Outlier detection in lithography: benchmarking and the creation of a new algorithmOutlier detectionAnomaly detectionLithographyEnsemble algorithmInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsOverlay is the measure of a lithography machine’s success at printing layers accurately atop one another. Poor overlay in semiconductor manufacturing can cause problems in a semiconductor chip’s electrical current and, in the worst case, can render the chips unusable. A new algorithm is proposed for detecting outliers in lithography calibration wafers using an ensemble of well-known statistical methods. Detecting outliers on these calibration wafers and removing them from the data fed to the lithography machine contributes to improving overlay accuracy for semiconductor manufacturers as these wafers are used to set proper alignment on a lithography machine. Through simulation, the new ensemble algorithm along with other outlier algorithms are benchmarked against a lithography firm’s current outlier detection algorithm. The new ensemble algorithm shows outperformance on every criterion tested.Bação, Fernando José Ferreira LucasNazarian, AlexeiRUNBrown, Monika Rose2023-06-02T00:30:38Z2020-06-022020-06-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/100950TID:202501124enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:47:17Zoai:run.unl.pt:10362/100950Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:39:27.959189Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
title |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
spellingShingle |
Outlier detection in lithography: benchmarking and the creation of a new algorithm Brown, Monika Rose Outlier detection Anomaly detection Lithography Ensemble algorithm |
title_short |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
title_full |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
title_fullStr |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
title_full_unstemmed |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
title_sort |
Outlier detection in lithography: benchmarking and the creation of a new algorithm |
author |
Brown, Monika Rose |
author_facet |
Brown, Monika Rose |
author_role |
author |
dc.contributor.none.fl_str_mv |
Bação, Fernando José Ferreira Lucas Nazarian, Alexei RUN |
dc.contributor.author.fl_str_mv |
Brown, Monika Rose |
dc.subject.por.fl_str_mv |
Outlier detection Anomaly detection Lithography Ensemble algorithm |
topic |
Outlier detection Anomaly detection Lithography Ensemble algorithm |
description |
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-06-02 2020-06-02T00:00:00Z 2023-06-02T00:30:38Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/100950 TID:202501124 |
url |
http://hdl.handle.net/10362/100950 |
identifier_str_mv |
TID:202501124 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799138010577502208 |