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Proceedings Paper

Lithographic process window analysis by statistical means
Author(s): Anatoly Bourov; Sergei V. Postnikov; Kevin Lucas
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Paper Abstract

In this paper, we discuss a methodology for characterizing and comparing the lithographic process from the CD control point of view. In contrast to the traditional method of exposure latitude vs. depth of focus widely used in lithography, we use the statistical line width variation Cpk, and Cp as the measures of the lithographic process performance and capability. We have developed a software package called Megastat, which estimates CD variation based on experimental focus and exposure matrix (Bossung Curves) and assumed or independently measured focus and dose stochastic behavior. A similar approach was considered in. The impact of focus and dose control on across chip line width variation (ACLV) and across wafer line width variation (AWLV) was quantified with Megastat and compared to the experimentally obtained CD control for a particular 248nm lithographic process for the 130nm technology node. The statistical approach utilized in the Megastat software produced a very good match with the experimental results, which confirmed the usefulness of the statistical approach to characterizing the lithographic processes. We have additionally devised methods for decoupling and determining the actual experimental statistical variations inherent in lithographic processes. These methods allow the input 1 sigma variations for the statistical window analysis to be accurately determined. The usefulness of these methods will also be shown.

Paper Details

Date Published: 16 July 2002
PDF: 8 pages
Proc. SPIE 4689, Metrology, Inspection, and Process Control for Microlithography XVI, (16 July 2002); doi: 10.1117/12.473487
Show Author Affiliations
Anatoly Bourov, Rochester Institute of Technology (United States)
Sergei V. Postnikov, Motorola (United States)
Kevin Lucas, Motorola (United States)


Published in SPIE Proceedings Vol. 4689:
Metrology, Inspection, and Process Control for Microlithography XVI
Daniel J. C. Herr, Editor(s)

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