AUTOMATIC DEFECT CLASSIFICATION WITH INVARIANT CORE CLASSES

Patent №

US 6,987,873

Granted

2006-01-17

Filed 1998

Owner

APPLIED MATERIALS, INC.

Lab

AI components

2

vision · planning

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09111454

A method and apparatus is provided for automatically classifying a defect on the surface of a semiconductor wafer into one of, e.g., seven core classes: a missing pattern on the surface, an extra pattern on the surface, a deformed pattern on the surface, a particle on the surface, a particle embedded in the surface, a particle and a deformed pattern on the surface, or craters and microscratches on the surface. The defect may also be further classified into a subclass of arbitrarily defined defects defined by the user or preprogrammed in the apparatus. Embodiments include using a scanning electron microscope (SEM) capable of collecting electrons emitted from a plurality of angular sectors to obtain an image of the defect and a reference image containing topographical and location information, then analyzing this information to classify the defect. As the defects are classified, counts are maintained of the number of occurrences of each type of defect, and an alarm is raised if the defect count in a particular class exceeds a predetermined level. Thus, defects are accurately and reliably classified and monitored to enable early detection and cure of processing problems.

VisionPlanningH01L 22/20H10P 74/23G01N 21/88H01L 2924/0002

AI classification

Planning1.00
Vision0.55
AI hardware0.03
Knowledge representation0.02
Machine learning0.00
Natural language0.00
Evolutionary computation0.00
Speech0.00

Ownership

APPLIED MATERIALS, INC.

assignment · 93900367

Assignors

BEN-PORATH, ARIEL, WAGNER, MARK

On an employer assignment, the assignors are typically the inventors.

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