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Equipment fault detection with fitted wafer surfaces
This paper describes a new methodology for equipment fault detection. This methodology consists of fitting a thin-plate spline to post-process spatial data in order to construct a virtual wafer surface. The virtual wafer surface is then compared to an established baseline process surface, and the re...
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| Format: | Conference Proceeding |
| Language: | English |
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| creator | Gardner, M.M. Lu, J.C. Gyuresik, R.S. Wortman, J.J. Hornung, B.E. Heinisch, H.H. Rying, E.A. |
| description | This paper describes a new methodology for equipment fault detection. This methodology consists of fitting a thin-plate spline to post-process spatial data in order to construct a virtual wafer surface. The virtual wafer surface is then compared to an established baseline process surface, and the resulting spatial signature is used to detect equipment faults. Statistical distributional studies of signature metrics using a parametric bootstrapping technique provide the justification of determining the significance of the signature. Data collected from a Rapid Thermal Chemical Vapor Deposition (RTCVD) process is used to illustrate the procedures. This method detected equipment faults for all 11 wafers that were subjected to induced equipment faults. |
| doi_str_mv | 10.1109/IEMT.1996.559758 |
| format | conference_proceeding |
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This methodology consists of fitting a thin-plate spline to post-process spatial data in order to construct a virtual wafer surface. The virtual wafer surface is then compared to an established baseline process surface, and the resulting spatial signature is used to detect equipment faults. Statistical distributional studies of signature metrics using a parametric bootstrapping technique provide the justification of determining the significance of the signature. Data collected from a Rapid Thermal Chemical Vapor Deposition (RTCVD) process is used to illustrate the procedures. This method detected equipment faults for all 11 wafers that were subjected to induced equipment faults.</description><identifier>ISSN: 1089-8190</identifier><identifier>ISBN: 0780336429</identifier><identifier>ISBN: 9780780336421</identifier><identifier>EISSN: 2576-9626</identifier><identifier>DOI: 10.1109/IEMT.1996.559758</identifier><language>eng</language><publisher>IEEE</publisher><subject>Chemical vapor deposition ; Degradation ; Fault detection ; Fault diagnosis ; Rapid thermal processing ; Semiconductor device modeling ; Semiconductor process modeling ; Spline ; Statistics ; Surface fitting</subject><ispartof>Nineteenth IEEE/CPMT International Electronics Manufacturing Technology Symposium, 1996, p.364-371</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/559758$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/559758$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Gardner, M.M.</creatorcontrib><creatorcontrib>Lu, J.C.</creatorcontrib><creatorcontrib>Gyuresik, R.S.</creatorcontrib><creatorcontrib>Wortman, J.J.</creatorcontrib><creatorcontrib>Hornung, B.E.</creatorcontrib><creatorcontrib>Heinisch, H.H.</creatorcontrib><creatorcontrib>Rying, E.A.</creatorcontrib><title>Equipment fault detection with fitted wafer surfaces</title><title>Nineteenth IEEE/CPMT International Electronics Manufacturing Technology Symposium</title><addtitle>IEMT</addtitle><description>This paper describes a new methodology for equipment fault detection. This methodology consists of fitting a thin-plate spline to post-process spatial data in order to construct a virtual wafer surface. The virtual wafer surface is then compared to an established baseline process surface, and the resulting spatial signature is used to detect equipment faults. Statistical distributional studies of signature metrics using a parametric bootstrapping technique provide the justification of determining the significance of the signature. Data collected from a Rapid Thermal Chemical Vapor Deposition (RTCVD) process is used to illustrate the procedures. This method detected equipment faults for all 11 wafers that were subjected to induced equipment faults.</description><subject>Chemical vapor deposition</subject><subject>Degradation</subject><subject>Fault detection</subject><subject>Fault diagnosis</subject><subject>Rapid thermal processing</subject><subject>Semiconductor device modeling</subject><subject>Semiconductor process modeling</subject><subject>Spline</subject><subject>Statistics</subject><subject>Surface fitting</subject><issn>1089-8190</issn><issn>2576-9626</issn><isbn>0780336429</isbn><isbn>9780780336421</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1996</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNp9jj0LwjAUAB9-gFW7i1P-QGvSJmnfLBUd3Nwl6AtGtNYmpfjvFXT2lhtuOYCF4KkQHFe7an9IBaJOlcJClQOIMlXoBHWmhzDlRcnzXMsMRxAJXmJSCuQTiL2_8g9SKokYgayenWvuVAdmTXcL7EyBTsE9ata7cGHWhUBn1htLLfNda82J_BzG1tw8xT_PYLmpDutt4ojo2LTubtrX8fuV_41vii84Iw</recordid><startdate>1996</startdate><enddate>1996</enddate><creator>Gardner, M.M.</creator><creator>Lu, J.C.</creator><creator>Gyuresik, R.S.</creator><creator>Wortman, J.J.</creator><creator>Hornung, B.E.</creator><creator>Heinisch, H.H.</creator><creator>Rying, E.A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1996</creationdate><title>Equipment fault detection with fitted wafer surfaces</title><author>Gardner, M.M. ; Lu, J.C. ; Gyuresik, R.S. ; Wortman, J.J. ; Hornung, B.E. ; Heinisch, H.H. ; Rying, E.A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_5597583</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Chemical vapor deposition</topic><topic>Degradation</topic><topic>Fault detection</topic><topic>Fault diagnosis</topic><topic>Rapid thermal processing</topic><topic>Semiconductor device modeling</topic><topic>Semiconductor process modeling</topic><topic>Spline</topic><topic>Statistics</topic><topic>Surface fitting</topic><toplevel>online_resources</toplevel><creatorcontrib>Gardner, M.M.</creatorcontrib><creatorcontrib>Lu, J.C.</creatorcontrib><creatorcontrib>Gyuresik, R.S.</creatorcontrib><creatorcontrib>Wortman, J.J.</creatorcontrib><creatorcontrib>Hornung, B.E.</creatorcontrib><creatorcontrib>Heinisch, H.H.</creatorcontrib><creatorcontrib>Rying, E.A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gardner, M.M.</au><au>Lu, J.C.</au><au>Gyuresik, R.S.</au><au>Wortman, J.J.</au><au>Hornung, B.E.</au><au>Heinisch, H.H.</au><au>Rying, E.A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Equipment fault detection with fitted wafer surfaces</atitle><btitle>Nineteenth IEEE/CPMT International Electronics Manufacturing Technology Symposium</btitle><stitle>IEMT</stitle><date>1996</date><risdate>1996</risdate><spage>364</spage><epage>371</epage><pages>364-371</pages><issn>1089-8190</issn><eissn>2576-9626</eissn><isbn>0780336429</isbn><isbn>9780780336421</isbn><abstract>This paper describes a new methodology for equipment fault detection. This methodology consists of fitting a thin-plate spline to post-process spatial data in order to construct a virtual wafer surface. The virtual wafer surface is then compared to an established baseline process surface, and the resulting spatial signature is used to detect equipment faults. Statistical distributional studies of signature metrics using a parametric bootstrapping technique provide the justification of determining the significance of the signature. Data collected from a Rapid Thermal Chemical Vapor Deposition (RTCVD) process is used to illustrate the procedures. This method detected equipment faults for all 11 wafers that were subjected to induced equipment faults.</abstract><pub>IEEE</pub><doi>10.1109/IEMT.1996.559758</doi></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1089-8190 |
| ispartof | Nineteenth IEEE/CPMT International Electronics Manufacturing Technology Symposium, 1996, p.364-371 |
| issn | 1089-8190 2576-9626 |
| language | eng |
| recordid | cdi_ieee_primary_559758 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Chemical vapor deposition Degradation Fault detection Fault diagnosis Rapid thermal processing Semiconductor device modeling Semiconductor process modeling Spline Statistics Surface fitting |
| title | Equipment fault detection with fitted wafer surfaces |
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