Edge normal process

• US 20050013474A1
• Filed: 07/14/2004
• Published: 01/20/2005
• Est. Priority Date: 07/14/2003
• Status: Active Grant

• Current Assignee: Onto Innovation Inc.
• Original Assignee: August Technology Corporation (Onto Innovation Inc.)
• Inventors: Sim, Hak Chuah
• Granted Patent: US 6,947,588 B2
• Time in Patent Office: Days
• US Class Current: 382/145
• CPC Class Codes: G01N 21/9503 Wafer edge inspection
• CPC Class Codes: G01R 31/2831 Testing of materials or semi-finished products, e.g. semiconductor wafers or substrates G01R31/318511 takes precedence; testing during manufacture H01L22/00
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection

Abstract

An edge inspection method for detecting defects on a wafer edge normal surface includes acquiring a set of digital images which captures a circumference of the wafer. An edge of the wafer about the circumference is determined. Each digital image is segmented into a plurality of horizontal bands. Adjacent edge clusters about the circumference of the wafer are combined into edge pixel bins. The edge pixel bins are analyzed via edge clusters analysis to identify defects. The edge pixel bins are also analyzed via blob analysis to determine defects.

Claims

1. An edge inspection method for detecting defects on a wafer edge normal surface, the method comprising:

acquiring a set of digital images capturing a circumference of the wafer;

determining an edge of the wafer about the circumference of the wafer;

segmenting each digital image into a plurality of horizontal bands;

combine adjacent edge clusters about the circumference of the wafer into edge pixel bins;

analyze the edge pixel bins via edge cluster analysis to identify defects; and

analyze the edge pixel bins via blob analysis to identify defects.

2. The method of claim 1 and further comprising:

normalizing the set of digital images; and

segmenting each normalized digital image into a plurality of horizontal bands.

3. The method of claim 1 and further comprising:

performing lateral illumination correction on each of the plurality of segmented horizontal bands.

4. The method of claim 3 wherein performing lateral illumination correction on each of the plurality of segmented horizontal bands further comprises:

subtracting an underlying local lateral illumination error for each of the plurality of segmented horizontal bands.

5. The method of claim 1 and further comprising:

creating a dynamic reference image of a defect-free wafer image.

6. The method of claim 5 wherein creating a dynamic reference image of a defect-free wafer image further comprises:

combining a vertical projection intensity and a local band lateral intensity variation, thereby creating the dynamic reference image.

7. The method of claim 1 and further comprising:

performing image edge analysis on the plurality of segmented horizontal bands.

8. The method of claim 1 wherein segmenting each digital image into a plurality of horizontal bands further comprises:

detecting intensity transitions in a vertical projection of mean pixel intensity on each scan line in the digital image.

9. The method of claim 1 wherein the step of combining adjacent edge clusters into edge pixel bins further comprises:

dividing each horizontal band into several overlapping vertical bins.

10. The method of claim 1 wherein analyzing the edge pixel bins via edge cluster analysis further comprises:

scanning the edge pixel bins for continuous sets of non-empty bins having an edge pixel count greater than 120% of an average edge pixel count; and

associating a single surface variation defect with a bound rectangular region about the edge cluster bin having an edge pixel count greater than 120%.

11. The method of claim 1 wherein the step of analyzing the edge pixel bins via blob analysis further comprises:

detecting blobs having pixel errors greater than 180% of the average pixel error.

12. The method of claim 1 and further comprising:

constructing a statistical model of defects for each of the plurality of segmented horizontal bands.

13. An edge inspection method for detecting defects on a wafer edge normal surface, the method comprising:

acquiring a set of digital images capturing a circumference of the wafer;

determining an edge of the wafer about the circumference of the wafer;

segmenting each digital image into a plurality of horizontal bands;

combine adjacent edge clusters about the circumference of the wafer into edge pixel bins; and

analyze the edge pixel bins via edge cluster analysis to identify defects.

14. The method of claim 13 and further comprising:

normalizing the set of digital images; and

segmenting each normalized digital image into a plurality of horizontal bands.

15. The method of claim 13 and further comprising:

performing lateral illumination correction on each of the plurality of segmented horizontal bands.

16. The method of claim 15 wherein performing lateral illumination correction on each of the plurality of segmented horizontal bands further comprises:

subtracting an underlying local lateral illumination error for each of the plurality of segmented horizontal bands.

17. The method of claim 13 and further comprising:

creating a dynamic reference image of a defect-free wafer image.

18. The method of claim 17 wherein creating a dynamic reference image of a defect-free wafer image further comprises:

combining a vertical projection intensity and a local band lateral intensity variation, thereby creating the dynamic reference image.

19. The method of claim 13 and further comprising:

performing image edge analysis on the plurality of segmented horizontal bands.

20. The method of claim 13 wherein segmenting each digital image into a plurality of horizontal bands further comprises:

detecting intensity transitions in a vertical projection of mean pixel intensity on each scan line in the digital image.

21. The method of claim 13 wherein the step of combining adjacent edge clusters into edge pixel bins further comprises:

dividing each horizontal band into several overlapping vertical bins.

22. The method of claim 13 wherein analyzing the edge pixel bins via edge cluster analysis further comprises:

scanning the edge pixel bins for continuous sets of non-empty bins having an edge pixel count greater than 120% of an average edge pixel count; and

associating a single surface variation defect with a bound rectangular region about the edge cluster bin having an edge pixel count greater than 120%.

23. The method of claim 13 and further comprising:

constructing a statistical model of defects for each of the plurality of segmented horizontal bands.

24. An edge inspection method for detecting defects on a wafer edge normal surface, the method comprising:

acquiring a set of digital images capturing a circumference of the wafer;

determining an edge of the wafer about the circumference of the wafer;

segmenting each digital image into a plurality of horizontal bands;

combine adjacent edge clusters about the circumference of the wafer into edge pixel bins; and

analyze the edge pixel bins via blob analysis to identify defects.

25. The method of claim 24 and further comprising:

normalizing the set of digital images; and

segmenting each normalized digital image into a plurality of horizontal bands.

26. The method of claim 24 and further comprising:

performing lateral illumination correction on each of the plurality of segmented horizontal bands.

27. The method of claim 26 wherein performing lateral illumination correction on each of the plurality of segmented horizontal bands further comprises:

subtracting an underlying local lateral illumination error for each of the plurality of segmented horizontal bands.

28. The method of claim 24 and further comprising:

creating a dynamic reference image of a defect-free wafer image.

29. The method of claim 28 wherein creating a dynamic reference image of a defect-free wafer image further comprises:

combining a vertical projection intensity and a local band lateral intensity variation, thereby creating the dynamic reference image.

30. The method of claim 24 and further comprising:

performing image edge analysis of a plurality of segmented horizontal bands.

31. The method of claim 24 wherein segmenting each digital image into a plurality of horizontal bands further comprises:

detecting intensity transitions in a vertical projection of mean pixel intensity on each scan line in the digital image.

32. The method of claim 24 wherein the step of combining adjacent edge clusters into edge pixel bins further comprises:

dividing each horizontal band into several overlapping vertical bins.

33. The method of claim 24 wherein the step of analyzing the edge pixel bins via blob analysis further comprises:

detecting blobs having pixel errors greater than 180% of the average pixel error.

34. The method of claim 24 and further comprising:

constructing a statistical model of defects for each of the plurality of segmented horizontal bands.