Metrology Sampling Strategies for Process Monitoring Applications

Handle URI:
http://hdl.handle.net/10754/598820
Title:
Metrology Sampling Strategies for Process Monitoring Applications
Authors:
Vincent, Tyrone L.; Stirton, James Broc; Poolla, Kameshwar
Abstract:
Shrinking process windows in very large scale integration semiconductor manufacturing have already necessitated the development of control systems capable of addressing sub-lot-level variation. Within-wafer control is the next milestone in the evolution of advanced process control from lot-based and wafer-based control. In order to adequately comprehend and control within-wafer spatial variation, inline measurements must be performed at multiple locations across the wafer. At the same time, economic pressures prompt a reduction in metrology, for both capital and cycle-time reasons. This paper explores the use of modeling and minimum-variance prediction as a method to select the sites for measurement on each wafer. The models are developed using the standard statistical tools of principle component analysis and canonical correlation analysis. The proposed selection method is validated using real manufacturing data, and results indicate that it is possible to significantly reduce the number of measurements with little loss in the information obtained for the process control systems. © 2011 IEEE.
Citation:
Vincent TL, Stirton JB, Poolla K (2011) Metrology Sampling Strategies for Process Monitoring Applications. IEEE Trans Semicond Manufact 24: 489–498. Available: http://dx.doi.org/10.1109/TSM.2011.2159139.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Semiconductor Manufacturing
KAUST Grant Number:
025478
Issue Date:
Nov-2011
DOI:
10.1109/TSM.2011.2159139
Type:
Article
ISSN:
0894-6507; 1558-2345
Sponsors:
This work was supported in part by the National Science Foundation, under Grants ECCS-0925337 and CNS-0931748, by OOF991-KAUST US Ltd., under Award 025478, and by the UC Discovery Grant ele07-10283, under the IMPACT Program.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorVincent, Tyrone L.en
dc.contributor.authorStirton, James Brocen
dc.contributor.authorPoolla, Kameshwaren
dc.date.accessioned2016-02-25T13:41:52Zen
dc.date.available2016-02-25T13:41:52Zen
dc.date.issued2011-11en
dc.identifier.citationVincent TL, Stirton JB, Poolla K (2011) Metrology Sampling Strategies for Process Monitoring Applications. IEEE Trans Semicond Manufact 24: 489–498. Available: http://dx.doi.org/10.1109/TSM.2011.2159139.en
dc.identifier.issn0894-6507en
dc.identifier.issn1558-2345en
dc.identifier.doi10.1109/TSM.2011.2159139en
dc.identifier.urihttp://hdl.handle.net/10754/598820en
dc.description.abstractShrinking process windows in very large scale integration semiconductor manufacturing have already necessitated the development of control systems capable of addressing sub-lot-level variation. Within-wafer control is the next milestone in the evolution of advanced process control from lot-based and wafer-based control. In order to adequately comprehend and control within-wafer spatial variation, inline measurements must be performed at multiple locations across the wafer. At the same time, economic pressures prompt a reduction in metrology, for both capital and cycle-time reasons. This paper explores the use of modeling and minimum-variance prediction as a method to select the sites for measurement on each wafer. The models are developed using the standard statistical tools of principle component analysis and canonical correlation analysis. The proposed selection method is validated using real manufacturing data, and results indicate that it is possible to significantly reduce the number of measurements with little loss in the information obtained for the process control systems. © 2011 IEEE.en
dc.description.sponsorshipThis work was supported in part by the National Science Foundation, under Grants ECCS-0925337 and CNS-0931748, by OOF991-KAUST US Ltd., under Award 025478, and by the UC Discovery Grant ele07-10283, under the IMPACT Program.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectAdvanced process controlen
dc.subjectcanonical correlation analysisen
dc.subjectprincipal component analysisen
dc.subjectsite samplingen
dc.subjectsystematic variationen
dc.subjectwithin-wafer controlen
dc.titleMetrology Sampling Strategies for Process Monitoring Applicationsen
dc.typeArticleen
dc.identifier.journalIEEE Transactions on Semiconductor Manufacturingen
dc.contributor.institutionColorado School of Mines, Golden, United Statesen
dc.contributor.institutionGLOBALFOUNDRIES U. S., , United Statesen
dc.contributor.institutionUC Berkeley, Berkeley, United Statesen
kaust.grant.number025478en
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