Method and apparatus for detecting defects in wafers

• US 20060193507A1
• Filed: 02/28/2005
• Published: 08/31/2006
• Est. Priority Date: 02/28/2005
• Status: Active Grant

• Current Assignee: Applied Materials South East Asia Pte Limited (Applied Materials Incorporated)
• Original Assignee: Negevtech Limited (Negevtech)
• Inventors: Yanir, Tomer, Dorfan, Yuval, Sali, Erez, Dotan, Noam, Wagner, Mark, Zaslavsky, Ran
• Granted Patent: US 7,813,541 B2
• Time in Patent Office: Days
• US Class Current: 382/145
• CPC Class Codes: G01N 21/9501 Semiconductor wafers manufacturing processes per se of semiconductor devices implementing a measuring step H01L22/10
• CPC Class Codes: G01N 21/95607 using a comparative method
• CPC Class Codes: G06T 7/001 using an image reference approach

Abstract

A method for inspecting a wafer including a multiplicity of dies, the method including dividing an image of at least a portion of the wafer into a plurality of sub-images each representing a sub-portion of the wafer and selecting at least one defect candidate within each sub-image by comparing each sub-image to a corresponding sub-image of a reference including a representation, which is assumed to be faultless, of the portion of the wafer.

Claims

1. A method for inspecting a wafer including a multiplicity of dies, the method comprising:

dividing an image of at least a portion of said wafer into a plurality of sub-images each representing a sub-portion of said wafer; and

selecting at least one defect candidate within each said sub-image, by comparing each sub-image to a corresponding sub-image of a reference comprising a representation, which is assumed to be defectless, of said portion of said wafer.

2. A method according to claim 1 and also comprising generating the reference by providing and aligning a plurality of images of the wafer and computing a median of the pixel values of the plurality of aligned images, at each pixel location.

3. A method according to claim 1 and also comprising performing further defect detection analysis on a subset of said defect candidates, said subset comprising a predetermined number of best defect candidates.

4. A method according to claim 1 and also comprising:

dividing at least one of said sub-images into portions which it is desired to inspect separately; and

for each portion, performing further defect detection analysis on a subset of said defect candidates belonging to said portion, said subset comprising a predetermined number of those defect candidates within said portion which have the highest difference values.

5. A method according to claim 4 wherein said image comprises patternless portions and wherein said step of selecting at least one defect candidate within each said sub-image comprises selecting the pixel within each said sub-image with the largest gray level value.

6. A method according to claim 4 wherein said image also comprises bright portions reflecting a large amount of light and wherein defect candidates are not selected within said bright portions.

7. A method according to claim 4 wherein said dividing step comprises dividing at least one of said sub-images into portions each having a defined gray level range in the reference.

8. A method according to claim 4 wherein said dividing step comprises dividing at least one of said sub-images into portions each having a defined gray level range in a gradient of the reference.

9. A method according to claim 4 wherein said dividing step comprises dividing at least one of said sub-images into portions, the portions having a defined gray level range in a difference image generated from a plurality of images of said portion of the wafer.

10. A method according to claim 9 wherein said difference image is generated by comparing an image of said portion of the wafer to another image of the same portion.

11. A method according to claim 1 wherein said selecting step comprises generating, for each sub-image, a difference sub-image representing the difference between the sub-image and a reference representing at least one identical sub-portion of the wafer and selecting at least one maximal difference value within said difference sub-image as a defect candidate.

12. A method according to claim 11 and also comprising performing further defect detection analysis on a subset of said defect candidates, said subset comprising a predetermined number of those defect candidates having the highest difference values.

16. A method according to claim 3 wherein said further defect detection analysis comprises identifying defect candidates which differ from their respectively corresponding locations in the reference image by more than a threshold value wherein said threshold value used for an individual defect candidate located at an individual location within said first image is a function of estimated noise between different images of said individual location.

17. A method according to claim 16 and also comprising estimating noise between different images of said individual location by estimating noise, at each of a multiplicity of locations, between at least two different images of each such location.

18. A method according to claim 17 wherein said step of estimating noise also comprises estimating noise, at each of a multiplicity of similar locations, between at least two different images of each such location.

19. A method according to claim 11 wherein said wafer portion comprises a multiplicity of cells each comprising a repeating portion of a pattern on the wafer, and wherein said identical sub-portion comprises at least a portion of a cell which is identical to a cell, within said sub-image, which is being inspected.

20. A method according to claim 1 and wherein said identical sub-portion comprises at least a portion of a die which is identical to a die, within said sub-image, which is being inspected.

34. A method according to claim 1 and wherein said comparing of each individual sub-image comprises comparing the individual sub-image to a reference image and identifying locations in the individual sub-image which differ from the reference image by more than a threshold value wherein said threshold value used for an individual location within said individual sub-image is a function of estimated noise between different images of said individual location.

35. A method according to claim 1 and wherein said selecting comprises:

inspecting a multiplicity of locations within each individual sub-image and selecting a plurality of defect candidates;

scoring said plurality of defect candidates and selecting a predetermined number of highest scoring defect candidates for further defect detection analysis.

36. A method according to claim 1 and wherein said selecting comprises:

for each of a multiplicity of locations in said sub-image, sorting discrepancies found between individual ones of a plurality of representations of said wafer locations into larger and smaller discrepancies; and

determining whether or not each location is a defect, based on the magnitude of at least one larger discrepancy for that location relative to the magnitude of at least one smaller discrepancy for that location.

37. A method according to claim 1 and wherein said comparing comprises:

generating a difference image comprising differences between a multiplicity of locations within the defective image and a corresponding multiplicity of locations within said reference, said difference image defining a distribution of difference values; and

selecting, as defects, individual ones from among said multiplicity of locations whose difference values are categorized as defects based on a defect definition function which is a predetermined function of said distribution of difference values.

38. A method according to claim 1 and also comprising generating said reference by providing at least three images of identical portions of said wafer, including adding smear to at least one of said images so as to generate an identical amount of smear in said at least three images, and combining said at least three images having identical amounts of smear, thereby to provide said reference.

13. A method for inspecting a wafer including a multiplicity of dies, the method comprising:

comparing a first image of at least a portion of the wafer to a reference image and identifying locations in the first image which differ from the reference image by more than a threshold value wherein said threshold value used for an individual location within said first image is a function of estimated noise between different images of said individual location.

14. A method according to claim 13 and also comprising estimating noise between different images of said individual location by estimating noise, at each of a multiplicity of locations, between at least two different images of each such location.

15. A method according to claim 14 and wherein said step of estimating noise comprises estimating noise at each of a multiplicity of similar locations, between at least two different images of each such location.

39. A method according to claim 13 and also comprising generating said reference image by providing at least three images of identical portions of said wafer, including adding smear to at least one of said images so as to generate an identical amount of smear in said at least three images, and combining said at least three images having identical amounts of smear, thereby to provide said reference image.

21. A method for inspecting at least a portion of a wafer comprising a multiplicity of dies comprising:

inspecting a multiplicity of locations within an image of at least a portion of said wafer to be inspected and selecting a plurality of defect candidates;

scoring the plurality of defect candidates and selecting a predetermined number of the highest scoring defect candidates for further defect detection analysis.

22. A method according to claim 21 wherein said inspecting step comprises comparing the multiplicity of locations within said at least a portion of said wafer to be inspected, with a multiplicity of references, and quantifying the differences therebetween, thereby to obtain a corresponding multiplicity of difference values characterizing the multiplicity of locations respectively.

23. A method according to claim 22 wherein said significant criterion comprises the signal to noise ratio of the image.

40. A method according to claim 21 wherein said defect candidates are selected and scored relative to a reference image, the method also comprising generating said reference image by providing at least three images of identical portions of said wafer, including adding smear to at least one of said images so as to generate an identical amount of smear in said at least three images, and combining said at least three images having identical amounts of smear, thereby to provide said reference image.

24. A method for inspecting a wafer including a multiplicity of dies comprising:

for each of a multiplicity of locations of the wafer, sorting discrepancies found between individual ones of a plurality of representations of said wafer location into larger and smaller discrepancies; and

determining whether or not each location is a defect, based on the magnitude of at least one larger discrepancy for that location relative to the magnitude of at least one smaller discrepancy for that location.

41. A method according to claim 24 and also comprising adding smear to at least one of said plurality of representations of said wafer location so as to generate an identical amount of smear in said plurality of representations.

25. A method for inspecting a defective image of a wafer including a multiplicity of dies, the method comprising:

generating a difference image comprising differences between a multiplicity of locations within the defective image and a corresponding multiplicity of locations within a reference, the difference image defining a distribution of difference values; and

selecting, as defects, individual ones from among said multiplicity of locations whose difference values are characterized as defects based on a defect definition function which is a predetermined function of said distribution of difference values.

26. A method according to claim 25 wherein the multiplicity of locations within the reference is divided into a plurality of bins each having defined characteristics, each bin defining a distribution of difference values at the locations in the difference image corresponding to the locations within that bin, and wherein said selecting step comprises selecting, as a defect, at least one individual location from among said multiplicity of locations whose difference value answers to a defect definition function which is a predetermined function of the distribution of difference values within the bin to which said individual location belongs.

27. A method according to claim 26 wherein said selecting step comprises selecting, as a defect, at least one individual set of adjacent locations whose difference values answer to a defect definition function which is a combination of predetermined functions of the distributions of difference values within the bins to which said adjacent locations respectively belong.

28. A method according to claim 27 wherein said set of adjacent locations comprises a matrix of adjacent pixels.

29. A method according to claim 27 wherein each said predetermined function of the distribution of difference values within a bin to which an adjacent location belongs comprises a function of an average of all difference values in the bin to which the adjacent location belongs which exceed a predetermined high percentile difference value within that bin.

30. A method according to claim 29 wherein each said predetermined function comprises a normalized function having a normalization factor based on the noise level within the bin to which the adjacent location, associated with the predetermined function, belongs.

31. A method according to claim 25 wherein said predetermined function comprises a multiple of a high percentile difference value.

32. A method according to claim 25 wherein said predetermined function comprises a multiple of a combination of a subset of high-value difference values.

33. A method according to claim 29 wherein said predetermined function comprises a multiple of an average of all difference values in the difference image which exceed a predetermined high percentile difference value.

42. A method according to claim 25 and also comprising generating said reference by providing at least three images of identical portions of said wafer, including adding smear to at least one of said images so as to generate an identical amount of smear in said at least three images, and combining said at least three images having identical amounts of smear, thereby to provide said reference.

43. Apparatus for inspecting a wafer including a multiplicity of dies comprising:

an image divider, operative to divide an image of at least a portion of said wafer into a plurality of sub-images each representing a sub-portion of said wafer; and

a defect candidate identifier, operative to select at least one defect candidate within each said sub-image by comparing each sub-image to a corresponding sub-image of a reference comprising a representation, which is assumed to be defectless, of said portion of said wafer.

44. Apparatus for inspecting a wafer including a multiplicity of dies comprising:

an image comparator, operative to compare a first image of at least a portion of the wafer to a reference image and to identify locations in the first image which differ from the reference image by more than a threshold value wherein said threshold value used for an individual location within said first image is a function of estimated noise between different images of said individual location.

45. Apparatus for inspecting a at least a portion of a wafer including a multiplicity of dies comprising:

a defect candidate identifier, operative to inspect a multiplicity of locations within an image of a wafer to be inspected and to select a plurality of defect candidates; and

a defect candidate analyzer, operative to score the plurality of defect candidates and to select a predetermined number of the highest scoring defect candidates for further defect detection analysis.

46. Apparatus for inspecting a wafer including a multiplicity of dies comprising:

a discrepancy sorter operative, for each of a multiplicity of locations of said wafer, to sort discrepancies found between individual ones of a plurality of representations of said wafer location into larger and smaller discrepancies; and

a discrepancy analyzer, operative to determine whether or not each location is a defect, based on the magnitude of at least one larger discrepancy for that location relative to the magnitude of at least one smaller discrepancy for that location.

47. Apparatus for inspecting a defective image of a wafer including a multiplicity of dies comprising:

a difference image generator, operative to generate a difference image comprising differences between a multiplicity of locations within the defective image and a corresponding multiplicity of locations within a reference, the difference image defining a distribution of difference values; and

a defect identifier operative to identify, as defects, individual ones from among said multiplicity of locations whose difference values are characterized as defects based on a defect definition function which is a predetermined function of said distribution of difference values.