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Proceedings Paper

Context-based virtual metrology
Author(s): Peter Ebersbach; Adam M. Urbanowicz; Dmitriy Likhachev; Carsten Hartig; Michael Shifrin
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Paper Abstract

Hybrid and data feed forward methodologies are well established for advanced optical process control solutions in highvolume semiconductor manufacturing. Appropriate information from previous measurements, transferred into advanced optical model(s) at following step(s), provides enhanced accuracy and exactness of the measured topographic (thicknesses, critical dimensions, etc.) and material parameters. In some cases, hybrid or feed-forward data are missed or invalid for dies or for a whole wafer. We focus on approaches of virtual metrology to re-create hybrid or feed-forward data inputs in high-volume manufacturing. We discuss missing data inputs reconstruction which is based on various interpolation and extrapolation schemes and uses information about wafer’s process history. Moreover, we demonstrate data reconstruction approach based on machine learning techniques utilizing optical model and measured spectra. And finally, we investigate metrics that allow one to assess error margin of virtual data input.

Paper Details

Date Published: 22 March 2018
PDF: 13 pages
Proc. SPIE 10585, Metrology, Inspection, and Process Control for Microlithography XXXII, 1058514 (22 March 2018); doi: 10.1117/12.2302498
Show Author Affiliations
Peter Ebersbach, GLOBALFOUNDRIES Dresden Module One LLC & Co. KG (Germany)
Adam M. Urbanowicz, Nova Measuring Instruments GmbH (Germany)
Dmitriy Likhachev, GLOBALFOUNDRIES Dresden Module One LLC & Co. KG (Germany)
Carsten Hartig, GLOBALFOUNDRIES Dresden Module One LLC & Co. KG (Germany)
Michael Shifrin, Nova Measuring Instruments Ltd. (Israel)


Published in SPIE Proceedings Vol. 10585:
Metrology, Inspection, and Process Control for Microlithography XXXII
Vladimir A. Ukraintsev, Editor(s)

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