Share Email Print

Proceedings Paper

Defect cluster analysis to detect equipment-specific yield loss based on yield-to-area calculations
Author(s): Christopher Hess; Larg H. Weiland
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top