Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment

To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Electronics (Basel) 2022-01, Vol.11 (2), p.253
Hauptverfasser: Kwon, Hyukjoon, Hong, Sang Jeen
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 2
container_start_page 253
container_title Electronics (Basel)
container_volume 11
creator Kwon, Hyukjoon
Hong, Sang Jeen
description To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or components of complicated semiconductor fabrication equipment are some of the most unnoticed factors that eventually change the plasma conditions. In this work, we propose improved stability and accuracy of process fault detection using optical emission spectroscopy (OES) data. Under a controlled experimental setup of arbitrarily induced fault scenarios, the extended isolation forest (EIF) approach was used to detect anomalies in OES data compared with the conventional isolation forest method in terms of accuracy and speed. We also used the OES data to generate features related to electron temperature and found that using the electron temperature features together with equipment status variable identification data (SVID) and OES data improved the prediction accuracy of process/equipment fault detection by a maximum of 0.84%.
doi_str_mv 10.3390/electronics11020253
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2621278099</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2621278099</sourcerecordid><originalsourceid>FETCH-LOGICAL-c388t-f769b942e9332f64697ab9fd3b7e9be875b9263241bb12c532d42b2cac1eb09e3</originalsourceid><addsrcrecordid>eNptkEFPwzAMhSMEEtPYL-ASiXMhcbq2PqKtA6ShIcHOVZKlolPadEkqtH9PxzhwwBdb8vee5UfILWf3QiB7MNbo6F3X6MA5AwZzcUEmwHJMEBAu_8zXZBbCno2FXBSCTUi3DYa6mm762Ghpadk2ITSuo-_9j2vQrj_SpYyS1s7TlRxspEsTx-WJGpWvMgS6su6LLlw3Kqw1njYdfbMytJKWUX_S8jA0fWu6eEOuammDmf32Kdmuyo_Fc7LePL0sHteJFkURkzrPUGEKBoWAOkszzKXCeidUblCZIp8rhExAypXioOcCdiko0FJzoxgaMSV3Z9_eu8NgQqz2bvDdeLKCDDjkBUMcKXGm9Pho8Kauet-00h8rzqpTttU_2Ypv4chwPA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2621278099</pqid></control><display><type>article</type><title>Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Kwon, Hyukjoon ; Hong, Sang Jeen</creator><creatorcontrib>Kwon, Hyukjoon ; Hong, Sang Jeen</creatorcontrib><description>To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or components of complicated semiconductor fabrication equipment are some of the most unnoticed factors that eventually change the plasma conditions. In this work, we propose improved stability and accuracy of process fault detection using optical emission spectroscopy (OES) data. Under a controlled experimental setup of arbitrarily induced fault scenarios, the extended isolation forest (EIF) approach was used to detect anomalies in OES data compared with the conventional isolation forest method in terms of accuracy and speed. We also used the OES data to generate features related to electron temperature and found that using the electron temperature features together with equipment status variable identification data (SVID) and OES data improved the prediction accuracy of process/equipment fault detection by a maximum of 0.84%.</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics11020253</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Algorithms ; Anomalies ; Artificial intelligence ; Electron energy ; Emission spectroscopy ; Fault detection ; Gas flow ; Manufacturing ; Mass flow ; Optical data processing ; Optical emission spectroscopy ; Plasma etching ; Process controls ; Recipes ; Sensors</subject><ispartof>Electronics (Basel), 2022-01, Vol.11 (2), p.253</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c388t-f769b942e9332f64697ab9fd3b7e9be875b9263241bb12c532d42b2cac1eb09e3</citedby><cites>FETCH-LOGICAL-c388t-f769b942e9332f64697ab9fd3b7e9be875b9263241bb12c532d42b2cac1eb09e3</cites><orcidid>0000-0002-6576-690X ; 0000-0002-2128-364X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Kwon, Hyukjoon</creatorcontrib><creatorcontrib>Hong, Sang Jeen</creatorcontrib><title>Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment</title><title>Electronics (Basel)</title><description>To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or components of complicated semiconductor fabrication equipment are some of the most unnoticed factors that eventually change the plasma conditions. In this work, we propose improved stability and accuracy of process fault detection using optical emission spectroscopy (OES) data. Under a controlled experimental setup of arbitrarily induced fault scenarios, the extended isolation forest (EIF) approach was used to detect anomalies in OES data compared with the conventional isolation forest method in terms of accuracy and speed. We also used the OES data to generate features related to electron temperature and found that using the electron temperature features together with equipment status variable identification data (SVID) and OES data improved the prediction accuracy of process/equipment fault detection by a maximum of 0.84%.</description><subject>Algorithms</subject><subject>Anomalies</subject><subject>Artificial intelligence</subject><subject>Electron energy</subject><subject>Emission spectroscopy</subject><subject>Fault detection</subject><subject>Gas flow</subject><subject>Manufacturing</subject><subject>Mass flow</subject><subject>Optical data processing</subject><subject>Optical emission spectroscopy</subject><subject>Plasma etching</subject><subject>Process controls</subject><subject>Recipes</subject><subject>Sensors</subject><issn>2079-9292</issn><issn>2079-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptkEFPwzAMhSMEEtPYL-ASiXMhcbq2PqKtA6ShIcHOVZKlolPadEkqtH9PxzhwwBdb8vee5UfILWf3QiB7MNbo6F3X6MA5AwZzcUEmwHJMEBAu_8zXZBbCno2FXBSCTUi3DYa6mm762Ghpadk2ITSuo-_9j2vQrj_SpYyS1s7TlRxspEsTx-WJGpWvMgS6su6LLlw3Kqw1njYdfbMytJKWUX_S8jA0fWu6eEOuammDmf32Kdmuyo_Fc7LePL0sHteJFkURkzrPUGEKBoWAOkszzKXCeidUblCZIp8rhExAypXioOcCdiko0FJzoxgaMSV3Z9_eu8NgQqz2bvDdeLKCDDjkBUMcKXGm9Pho8Kauet-00h8rzqpTttU_2Ypv4chwPA</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Kwon, Hyukjoon</creator><creator>Hong, Sang Jeen</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-6576-690X</orcidid><orcidid>https://orcid.org/0000-0002-2128-364X</orcidid></search><sort><creationdate>20220101</creationdate><title>Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment</title><author>Kwon, Hyukjoon ; Hong, Sang Jeen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-f769b942e9332f64697ab9fd3b7e9be875b9263241bb12c532d42b2cac1eb09e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Anomalies</topic><topic>Artificial intelligence</topic><topic>Electron energy</topic><topic>Emission spectroscopy</topic><topic>Fault detection</topic><topic>Gas flow</topic><topic>Manufacturing</topic><topic>Mass flow</topic><topic>Optical data processing</topic><topic>Optical emission spectroscopy</topic><topic>Plasma etching</topic><topic>Process controls</topic><topic>Recipes</topic><topic>Sensors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kwon, Hyukjoon</creatorcontrib><creatorcontrib>Hong, Sang Jeen</creatorcontrib><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Electronics (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kwon, Hyukjoon</au><au>Hong, Sang Jeen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment</atitle><jtitle>Electronics (Basel)</jtitle><date>2022-01-01</date><risdate>2022</risdate><volume>11</volume><issue>2</issue><spage>253</spage><pages>253-</pages><issn>2079-9292</issn><eissn>2079-9292</eissn><abstract>To minimize wafer yield losses by misprocessing during semiconductor manufacturing, faster and more accurate fault detection during the plasma process are desired to increase production yields. Process faults can be caused by abnormal equipment conditions, and the performance drifts of the parts or components of complicated semiconductor fabrication equipment are some of the most unnoticed factors that eventually change the plasma conditions. In this work, we propose improved stability and accuracy of process fault detection using optical emission spectroscopy (OES) data. Under a controlled experimental setup of arbitrarily induced fault scenarios, the extended isolation forest (EIF) approach was used to detect anomalies in OES data compared with the conventional isolation forest method in terms of accuracy and speed. We also used the OES data to generate features related to electron temperature and found that using the electron temperature features together with equipment status variable identification data (SVID) and OES data improved the prediction accuracy of process/equipment fault detection by a maximum of 0.84%.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/electronics11020253</doi><orcidid>https://orcid.org/0000-0002-6576-690X</orcidid><orcidid>https://orcid.org/0000-0002-2128-364X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2079-9292
ispartof Electronics (Basel), 2022-01, Vol.11 (2), p.253
issn 2079-9292
2079-9292
language eng
recordid cdi_proquest_journals_2621278099
source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Algorithms
Anomalies
Artificial intelligence
Electron energy
Emission spectroscopy
Fault detection
Gas flow
Manufacturing
Mass flow
Optical data processing
Optical emission spectroscopy
Plasma etching
Process controls
Recipes
Sensors
title Use of Optical Emission Spectroscopy Data for Fault Detection of Mass Flow Controller in Plasma Etch Equipment
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T05%3A17%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Use%20of%20Optical%20Emission%20Spectroscopy%20Data%20for%20Fault%20Detection%20of%20Mass%20Flow%20Controller%20in%20Plasma%20Etch%20Equipment&rft.jtitle=Electronics%20(Basel)&rft.au=Kwon,%20Hyukjoon&rft.date=2022-01-01&rft.volume=11&rft.issue=2&rft.spage=253&rft.pages=253-&rft.issn=2079-9292&rft.eissn=2079-9292&rft_id=info:doi/10.3390/electronics11020253&rft_dat=%3Cproquest_cross%3E2621278099%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2621278099&rft_id=info:pmid/&rfr_iscdi=true