FLEXIBLE HYBRID DEFECT CLASSIFICATION FOR SEMICONDUCTOR MANUFACTURING

• US 20060265145A1
• Filed: 09/30/2004
• Published: 11/23/2006
• Est. Priority Date: 09/30/2004
• Status: Active Grant

• Current Assignee: Kla-Tencor Technologies Corporation (KLA Corporation)
• Original Assignee: Kla-Tencor Technologies Corporation (KLA Corporation)
• Inventors: Kulkarni, Ashok, Zhang, Jianxin, Huang, Tong, Gao, Lisheng, Kowalski, Michal, Randall, David, Huet, Patrick, Wu, Kenong, Tribble, Ariel, McCauley, Sharon, Shanbhag, Maruti, Campochiaro, Cecelia Anne, Bhagwat, Sandeep, Kini, Vivekanand
• Granted Patent: US 7,142,992 B1
• Time in Patent Office: Days
• US Class Current: 702/35
• CPC Class Codes: G01R 31/2846 using hard- or software simulation or using knowledge-based systems, e.g. expert systems, artificial intelligence or interactive algorithms
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection

Abstract

Hybrid methods for classifying defects in semiconductor manufacturing are provided. The methods include applying a flexible sequence of rules for defects to inspection data. The sequence of rules includes deterministic rules, statistical rules, hybrid rules, or some combination thereof. The rules included in the sequence may be selected by a user using a graphical interface The method also includes classifying the defects based on results of applying the sequence of rules to the inspection data.

Claims

1. A flexible computer-implemented method for classifying defects, comprising:

applying a sequence of rules for defects to inspection data generated by inspection of a semiconductor specimen, wherein the sequence of rules comprises statistical rules, deterministic rules, hybrid statistical and deterministic rules, or some combination thereof, wherein a portion of the sequence of rules is applied as the defects are found during the inspection, and wherein another portion of the sequence of rules is applied at the end of the inspection;

classifying the defects based on results of said applying, wherein results of said classifying comprise multiple output classifications for the defects; and

illustrating the results of said classifying in an interactive user interface.

2. The method of claim 1, wherein the deterministic rules apply one or more tests to characteristics of the defects, and wherein the characteristics comprise whether the defects are bright or dark, contrast of the defects with respect to background, measured size, detection method, information about defects on other levels of the specimen, location of the defects on the specimen, proximity to other events, or some combination of attributes that can be used deterministically to classify defects.

3. The method of claim 1, wherein the statistical rules are based on characteristics of the defects comprising color, size, edge sharpness, eccentricity, roundness, transparency, texture, context, or some combination thereof, and wherein the statistical rules apply the characteristics statistically to bin defects.

4. The method of claim 1, wherein characteristics of the defects input to the statistical rules and the deterministic rules used for said applying are selected by a user.

5. The method in claim 1, wherein the another portion of the sequence of rules comprises rules based on proximity of the defects to other defects on the specimen or previous specimen history, and wherein dependent rules are applied after the another portion is applied.

6. The method of claim 1, wherein said applying is performed while a user is reviewing the defects.

7. The method of claim 1, further comprising tuning inspection recipes based on the results of said classifying.

8. The method of claim 1, further comprising using the results of said classifying in sampling defects for a subsequent activity.

9. The method of claim 1, further comprising performing engineering analysis using the results of said classifying.

10. The method of claim 1, further comprising performing the computer-implemented method on data generated by different inspection or review tools having different hardware configurations.

12. The method of claim 1, wherein said classifying comprises determining if the defects are nuisance defects based on results of said applying the deterministic rules or a combination of the deterministic and statistical rules.

13. The method of claim 1, wherein the statistical rules and the hybrid statistical and deterministic rules are organized into groups for selection to aid in user understanding of these rules and to provide classifications that reflect intent of a user.

14. The method of claim 1, wherein the statistical rules are weighted separately.

15. The method of claim 1, wherein the sequence of rules is organized by a user working with the interactive user interface, and wherein the sequence of rules is represented in the interactive user interface as a tree having different levels.

16. The method of claim 15, wherein the tree comprises nodes that produce one or more branches, one or more terminating bins, or some combination thereof.

17. The method of claim 15, wherein the tree comprises deterministic nodes, statistical nodes, or hybrid deterministic and statistical nodes.

18. The method of claim 15, wherein the tree comprises deterministic nodes designated by characteristic name, statistical nodes designated by name, and hybrid nodes designated by name.

19. The method of claim 15, wherein the interactive user interface illustrates the results of said classifying graphically and with sample images.

20. The method in claim 15, further comprising building one of the deterministic rules using the interactive user interface through applying unrestricted Boolean operators to defect characteristics.

11. (canceled)