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Proceedings Paper

Defect cluster analysis to detect equipment-specific yield loss based on yield-to-area calculations
Author(s): Christopher Hess; Larg H. Weiland
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Paper Abstract

Defect parameter extraction plays an important role in process control and yield prediction. A methodology of evaluating wafer level defect clustering will be presented to detect equipment specific particle contamination. For that, imaginary wafermaps of a variety of different chip areas are generated to calculate a yield-to-area dependency. Based on these calculations a Micro Density Distribution (MDD) will be determined for each wafer. The range and course of the MDD may indicate specific failures of equipment tools.

Paper Details

Date Published: 11 September 1997
PDF: 12 pages
Proc. SPIE 3216, Microelectronic Manufacturing Yield, Reliability, and Failure Analysis III, (11 September 1997); doi: 10.1117/12.284694
Show Author Affiliations
Christopher Hess, Univ. Karlsruhe (Germany)
Larg H. Weiland, Univ. Karlsruhe (Germany)


Published in SPIE Proceedings Vol. 3216:
Microelectronic Manufacturing Yield, Reliability, and Failure Analysis III
Ali Keshavarzi; Sharad Prasad; Hans-Dieter Hartmann, Editor(s)

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