Patent №
US 7,201,799
Granted
2007-04-10
Filed 2004
Owner
KLA-TENCOR TECHNOLOGIES
Lab
—
AI components
1
vision
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
10997328
An automated, non-invasive method for classifying, detecting, and counting micropipes contained within silicon wafers, and generally any assortment of transparent wafers. Classifying, detecting, and counting micropipes takes place through the use of a data processing algorithm that incorporates information regarding: defect size; pit signature; area of pit signature when comparing a topography, specular, or scatter images; and detecting a tail within the standard pit signature. The method of the present invention teaches the development of a topography defect map, specular defect map, and scatter defect map for a complete analysis of the surface of a particular transparent wafer. Conventional detection, classification, and counting of micropipes involve characterization of micropipes in a manual fashion and rely upon an extremely invasive form of sample preparation. The method disclosed in the present invention is completely automated and non-invasive with regards to the treatment of the transparent wafer to be analyzed.
AI classification
Ownership
KLA-TENCOR TECHNOLOGIES
assignment · 156280125
Assignors
VELIDANDLA, VAMSI
On an employer assignment, the assignors are typically the inventors.