Defect Review Sampling and Normalization Based on Defect and Design Attributes

Patent metadata

Field	Value
Publication number	US-2018107903-A1
Application number	US-201715426138-A
Country	US
Kind code	A1
Filing date	Feb 7, 2017
Priority date	Oct 14, 2016
Publication date	Apr 19, 2018
Grant date	—

Abstract

A decision tree and normalized reclassification are used to classify defects. Defect review sampling and normalization can be used for accurate Pareto ranking and defect source analysis. A defect review system, such as a broadband plasma tool, and a controller can be used to bin defects using the decision tree based on defect attributes and design attributes. Class codes are assigned to at least some of the defects in each bin. Normalized reclassification assigns a class code to any unclassified defects in a bin. Additional decision trees can be used if any bin has more than one class code after normalized reclassification.

First claim

What is claimed is:

1 . A system comprising:
a defect review system, wherein the defect review system includes:
a stage configured to hold a wafer; and
an image generation system configured to generate an image of the wafer; and
a controller in electronic communication with the defect review system, wherein the controller is configured to:
bin a plurality of defects into a plurality of bins using a decision tree based on defect attributes and design attributes;
assign one of one or more class codes to at least some of the defects in each of the bins, wherein each of the class codes represents a different defect type; and
perform normalized reclassification on each of the bins, wherein unclassified defects in the bins are each assigned one of the one or more class codes.

2 . The system of claim 1 , wherein the controller includes a processor, an electronic data storage unit in electronic communication with the processor, and a communication port in electronic communication with the processor and the electronic data storage unit.

3 . The system of claim 1 , wherein the defect review system is a broadband plasma tool.

4 . The system of claim 1 , wherein the image generation system is configured to use at least one of an electron beam, a broadband plasma, or a laser to generate the image of the wafer.

5 . The system of claim 1 , wherein one of the bins includes two of the class codes after the normalized reclassification, and wherein the controller is further configured to:
determine that one of the bins includes two of the class codes after the normalized reclassification; bin the defects in the bin with two of the class codes into a plurality of secondary bins using a secondary decision tree based on secondary defect attributes and secondary design attributes; assign one of one or more secondary class codes to at least some of the defects in each of the secondary bins, wherein each of the secondary class codes represents a different defect type; and perform normalized reclassification on each of the secondary bins, wherein unclassified defects in the secondary bins are each assigned one of the one or more secondary class codes.

6 . The system of claim 1 , wherein the defect attributes include one or more of attributes extracted from patch image processing algorithms, inspector optical attributes, inspector recipe attributes, wafer level signature attributes, zonal attributes, care area information, metrology attributes, process conditions, process equipment, and user-defined attributes, and wherein the design attributes include one or more of design-based class, design-based grouping, pattern grouping, hotspot grouping, design criticality index, pattern complexity index, and region of interest.

7 . A method comprising:
binning, using a controller, a plurality of defects from a semiconductor wafer into a plurality of bins using a decision tree based on defect attributes and design attributes; assigning, using the controller, one of one or more class codes to at least some of the defects in each of the bins, wherein each of the class codes represents a different defect type; and performing, using the controller, normalized reclassification on each of the bins, wherein unclassified defects in the bins are each assigned one of the one or more class codes.

8 . The method of claim 7 , wherein the defect attributes include one or more of attributes extracted from patch image processing algorithms, inspector optical attributes, inspector recipe attributes, wafer level signature attributes, zonal attributes, care area information, metrology attributes, process conditions, process equipment, and user-defined attributes, and wherein the design attributes include one or more of design-based class, design-based grouping, pattern grouping, hotspot grouping, design criticality index, pattern complexity index, and region of interest.

9 . The method of claim 7 , wherein a number of the defects per bin is distributed proportionally after the binning.

10 . The method of claim 7 , wherein one of the bins includes two of the class codes after the normalized reclassification, and further comprising:
determining, using the controller, that one of the bins includes two of the class codes after the normalized reclassification; binning, using the controller, the defects in the bin with two of the class codes into a plurality of secondary bins using a secondary decision tree based on secondary defect attributes and secondary design attributes; assigning, using the controller, one of one or more secondary class codes to at least some of the defects in each of the secondary bins, wherein each of the secondary class codes represents a different defect type; and performing, using the controller, normalized reclassification on each of the secondary bins, wherein unclassified defects in the secondary bins are each assigned one of the one or more secondary class codes.

11 . The method of claim 7 , further comprising inspecting a wafer for defects and communicating the plurality of defects on the wafer to the controller for binning.

12 . A non-transitory computer-readable storage medium, comprising one or more programs for executing the following steps on one or more computing devices:
bin a plurality of defects from a semiconductor wafer into a plurality of bins using a decision tree based on defect attributes and design attributes; assign one of one or more class codes to at least some of the defects in each of the bins, wherein each of the class codes represents a different defect type; and perform normalized reclassification on each of the bins, wherein unclassified defects in the bins are each assigned one of the one or more class codes.

13 . The non-transitory computer-readable storage medium of claim 12 , wherein a number of the defects per bin is distributed proportionally after the binning.

14 . The non-transitory computer-readable storage medium of claim 12 , wherein the defect attributes include one or more of attributes extracted from patch image processing algorithms, inspector optical attributes, inspector recipe attributes, wafer level signature attributes, zonal attributes, care area information, metrology attributes, process conditions, process equipment, and user-defined attributes, and wherein the design attributes include one or more of design-based class, design-based grouping, pattern grouping, hotspot grouping, design criticality index, pattern complexity index, and region of interest.

15 . The non-transitory computer-readable storage medium of claim 12 , wherein one of the bins includes two of the class codes after the normalized reclassification, and further comprising one or more programs for executing the following steps on one or more computing devices:
determine that one of the bins includes two of the class codes after the normalized reclassification; bin the defects in the bin with two of the class codes into a plurality of secondary bins using a secondary decision tree based on secondary defect attributes and secondary design attributes; assign one of one or more secondary class codes to at least some of the defects in each of the secondary bins, wherein each of the secondary class codes represents a different defect type; and perform normalized reclassification on each of the secondary bins, wherein unclassified defects in the secondary bins are each assigned one of the one or more secondary class codes.

Assignees

• Kla Tencor Corp

Inventors

• Yong Poh Boon

Classifications

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06F18/24323

  Tree-organised classifiers · CPC title

• G06T7/0006 Primary

  using a design-rule based approach · CPC title

• G06V10/44

  Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components · CPC title

• G06K9/4604

  Physics · mapped topic