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US 11,379,969 B2Granted
Method for process monitoring with optical inspections
AssigneeKLA Corporation
InventorsMartin Plihal, Prasanti Uppaluri, Saravanan Paramasivam
Life of this patent
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Abstract
Machine learning approaches provide additional information about semiconductor wafer inspection stability issues that makes it possible to distinguish consequential process variations like process excursions from minor process variations that are within specification. The effect of variable defect of interest (DOI) capture rates in the inspection result and the effect of variable defect count on the wafer can be monitored independently.
Claims18
A method comprising:
- optically inspecting a plurality of wafers with an optical inspection tool thereby generating images;
- extracting features from the images with machine learning-based classifiers using a processor;
- determining, using the processor, monitoring metrics from the features and a population of all detected events for the wafer;
- receiving, at the processor, classified defects of the wafers from a scanning electron microscope;
- determining, using the processor, separability metrics for the classified defects in relation to inspection thresholds, wherein the separability metrics account for a population distribution of the classified defects;
- and
- determining, using the processor, separability trends of the defects for the wafers.
4 more elements
A system comprising:
- an optical inspection tool including:
- a light source
- a stage configured to hold a wafer;
- and
- a detector;
- and
- a processor in electronic communication with the detector, wherein the processor is configured to:
- generate images of a plurality of the wafers using data from the detector;
- extract features from the images with machine learning-based classifiers using a processor;
- determine monitoring metrics from the features and a population of all detected events for the wafer;
- receive classified defects of the wafers from a scanning electron microscope;
- determine separability metrics for the classified defects in relation to inspection thresholds, wherein the separability metrics account for a population distribution of the classified defects;
- and
- determine separability trends of the defects for the wafers.
11 more elements
Dependencies are inferred from the claim text.