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Context-based automated defect classification system using multiple morphological masks

Patent ·
OSTI ID:874768
 [1];  [1];  [2]
  1. Knoxville, TN
  2. Lubbock, TX
+ Show Author Affiliations

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

Research Organization:
LOCKHEED MARTIN ENERGY RES COR
DOE Contract Number:
AC05-96OR22464
Assignee:
UT-Battelle, LLC (Oak Ridge, TN)
Patent Number(s):
US 6456899
OSTI ID:
874768
Country of Publication:
United States
Language:
English

References (4)

Automatic defect classification system for semiconductor wafers
  • Sherman, Rivi; Tirosh, Ehud; Smilansky, Zeev
  • IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, SPIE Proceedings https://doi.org/10.1117/12.144824
conference May 1993
Automatic classification of defects in semiconductor devices conference June 1990
Subpixel measurement of image features based on paraboloid surface fit conference March 1991
Nonlinear filter derived from topological image features conference September 1990

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