Computer-implemented methods and systems for classifying defects on a specimen

• US 20060082763A1
• Filed: 10/12/2005
• Published: 04/20/2006
• Est. Priority Date: 10/12/2004
• Status: Active Grant

• Current Assignee: Kla-Tencor Technologies Corporation (KLA Corporation)
• Original Assignee: Kla-Tencor Technologies Corporation (KLA Corporation)
• Inventors: Zhang, Jianxin, Huang, Tong, Gao, Lisheng, Kowalski, Michal, Balasubramanian, Lalita A., Oakley, Jonathan, Teh, Cho Huak, Yeung, Chiuman, David, Dominic, Torelli, Tommaso, Scott, Michael Gordon
• Granted Patent: US 8,532,949 B2
• Time in Patent Office: Days
• US Class Current: 356/72
• CPC Class Codes: G01N 21/9501 Semiconductor wafers manufacturing processes per se of semiconductor devices implementing a measuring step H01L22/10
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection

Abstract

Various computer-implemented methods for classifying defects on a specimen are provided. One method includes assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects. The method also includes displaying information about the defect groups to a user. In addition, the method includes allowing the user to assign a classification to each of the defect groups. Systems configured to classify defects on a specimen are also provided. One system includes program instructions executable on a processor for assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects. The system also includes a user interface configured for displaying information about the defect groups to a user and allowing the user to assign a classification to each of the defect groups.

Claims

1. A computer-implemented method for classifying defects on a specimen, comprising:

assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects;

displaying information about the defect groups to a user; and

allowing the user to assign a classification to each of the defect groups.

2. The method of claim 1, wherein the one or more characteristics comprise defect feature vectors, extracted features, feature attributes, or some combination thereof.

3. The method of claim 1, wherein the one or more characteristics are determined from data generated by electron beam review of the individual defects.

4. The method of claim 1, wherein the one or more characteristics are determined from data generated by electron beam review of the individual defects in combination with data generated by optical inspection of the specimen.

5. The method of claim 1, further comprising selecting a classification recipe based on one or more characteristics of the specimen, wherein said assigning comprises using the classification recipe to assign the individual defects to the defect groups.

6. The method of claim 1, further comprising selecting a classification recipe based on one or more processes performed on the specimen, wherein said assigning comprises using the classification recipe to assign the individual defects to the defect groups.

7. The method of claim 1, wherein said assigning comprises using automatic defect classification codes to assign the individual defects to the defect groups.

8. The method of claim 1, wherein said assigning comprises using natural grouping to assign the individual defects to the defect groups.

9. The method of claim 1, wherein the defect groups comprise a defect group for the individual defects that have one or more unrecognized characteristics.

10. The method of claim 1, wherein the defect groups comprise a defect group for the individual defects that were detected by inspection but were not re-detected by review.

11. The method of claim 1, wherein the information comprises probable classifications for the defect groups.

12. The method of claim 1, wherein the information comprises information about one or more typical defects included in each of the defect groups.

13. The method of claim 1, wherein the information comprises data about one or more of the individual defects, and wherein the data is generated by an electron beam review tool.

14. The method of claim 1, wherein the information comprises data about one or more of the individual defects, and wherein the data is generated by an optical inspection tool.

15. The method of claim 1, further comprising allowing the user to move one or more of the individual defects from one of the defect groups to another of the defect groups.

16. The method of claim 1, further comprising allowing the user to create one or more additional defect groups and to move one or more of the individual defects from the defect groups into the one or more additional defect groups.

17. The method of claim 1, further comprising generating a classification recipe based on the classifications assigned by the user, wherein the classification recipe can be used in semi-automatic defect classification methods and automatic defect classification methods.

18. The method of claim 1, wherein said assigning comprises using a classification recipe to assign the individual defects to the defect groups, the method further comprising altering the classification recipe based on the classifications assigned by the user.

19. The method of claim 1, further comprising generating a training set based on the classifications assigned by the user.

20. The method of claim 1, further comprising analyzing the individual defects, the specimen, processes performed on the specimen, or a combination thereof based on the classifications assigned by the user.

21. The method of claim 1, further comprising making yield management decisions based on the classifications assigned by the user.

22. A computer-implemented method for classifying defects on a specimen, comprising:

assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects;

displaying information about the defect groups to a user, wherein the information comprises a classification assigned to each of the defect groups; and

allowing the user to confirm or alter the classification assigned to each of the defect groups.

23. A system configured to classify defects on a specimen, comprising:

program instructions executable on a processor for assigning individual defects detected on the specimen to defect groups based on one or more characteristics of the individual defects; and

a user interface configured for displaying information about the defect groups to a user and allowing the user to assign a classification to each of the defect groups.

24. The system of claim 23, wherein said allowing comprises allowing the user to confirm or reject a classification that is assigned to each of the defect groups by the program instructions.

25. The system of claim 23, wherein said allowing comprising allowing the user to alter a classification that is assigned to each of the defect groups by the program instructions.