Inline defect analysis for sampling and SPC

• US 20080295048A1
• Filed: 05/22/2008
• Published: 11/27/2008
• Est. Priority Date: 05/24/2007
• Status: Active Grant

• Current Assignee: Applied Materials Incorporated
• Original Assignee: Applied Materials Incorporated
• Inventors: Schwarm, Alexander T., Shimshi, Rinat, Svidenko, Vicky, Jawaharlal, Sundar, Nehmadi, Youval
• Granted Patent: US 8,799,831 B2
• Time in Patent Office: Days
• US Class Current: 716/136
• CPC Class Codes: G01R 31/318511 Wafer Test

Abstract

In one embodiment, an inline defect analysis method includes receiving geometric characteristics of individual defects and design data corresponding to the individual defects, determining which of the individual defects are likely to be nuisance defects using the geometric characteristics and the corresponding design data, and refraining from sampling the defects that are likely to be nuisance defects.

Claims

1. A computer-implemented method comprising:

receiving geometric characteristics of individual defects and design data corresponding to the individual defects;

determining which of the individual defects are likely to be nuisance defects using the geometric characteristics and the corresponding design data; and

refraining from sampling the defects that are likely to be nuisance defects.

2. The computer-implemented method of claim 1, wherein determining which of the individual defects are likely to be nuisance defects comprises:

separating the individual defects into systematic defects and random defects;

determining which random defects are likely to be nuisance defects; and

determining which systematic defects are likely to be nuisance defects.

3. The computer-implemented method of claim 2, wherein the individual defects are separated into systematic defects and random defects using design-based binning.

4. The computer-implemented method of claim 2, wherein determining which random defects are likely to be nuisance defects comprises:

calculating a criticality factor (CF) value for the individual random defects using the geometric characteristics and design data of the individual random defects; and

comparing the CF value for the individual random defects to a predefined threshold.

5. The computer-implemented method of claim 4, further comprising:

selecting random defects with a CF value that exceeds the predefined threshold for sampling.

6. The computer-implemented method of claim 4, wherein calculating the CF value comprises:

identifying an open area, wherein the open area is a total area of all locations inside a design layout area to cause an open failure, and identifying a short area, wherein the short area is a total area of all locations inside the design layout to cause a short failure; and

calculating a probability of the random defect to cause an open failure and a probability of the random defect to cause a short failure.

7. The computer-implemented method of claim 2, wherein determining which systematic defects are likely to be nuisance defects comprises:

comparing systematic defects assigned to a structural bin to historical data for defects of previous structural bins; and

determining whether the systematic defects assigned to the structural bin are systematic defects already known to be nuisance defects based on the historical data.

8. The computer-implemented method of claim 1, wherein the geometric characteristics of the individual defects include at least one of:

a size of the defects, a volume of the defects, and a location of the defects within a design.

9. The computer-implemented method of claim 1, wherein the design data includes at least one of:

a layout of a design on which the defect is found and routing information for the design on which the defect is found.

10. A computer-implemented system comprising:

a design data database, to store design data for individual defects located within a design, wherein the design data includes at least one of;

a layout of the design on which the defect is found and routing information for the design on which the defect is found; and

an inline defect analyzer, coupled to the design data database, to determine which defects are likely to be nuisance defects and to refrain from sampling the individual defects that are likely to be nuisance defects.

11. The computer-implemented system of claim 10, further comprising:

a defect reporter, to provide geometric characteristics of the individual defects, wherein the geometric characteristics include at least one of;

a size of the defects, a volume of the defects, and a location of the defects within a design.

12. The computer-implemented system of claim 10, further comprising:

a defect review tool, to refrain from sampling the defects likely to be nuisance defects.

13. The computer-implemented system of claim 10, wherein the inline defect analyzer comprises:

a nuisance defect detector, to determine which of the individual defects are likely to be nuisance defects; and

a defect review selector, to select the defects likely to be nuisance defects for sampling.

14. The computer-implemented system of claim 13, wherein the nuisance defect detector determines which defects are likely to be nuisance defects by:

separating the individual defects into systematic defects and random defects;

determining which random defects are likely to be nuisance defects; and

determining which systematic defects are likely to be nuisance defects.

15. The computer-implemented system of claim 14, wherein the nuisance defect detector includes a defect separator to separate the individual defects into systematic defects and random defects using design-based binning.

16. The computer-implemented system of claim 14, wherein the nuisance defect detector includes a criticality factor calculator to calculate a criticality factor (CF) value for the individual random defects using the geometric characteristics and design data of the individual random defects to determine which random defects are likely to be nuisance defects.

17. The computer-implemented system of claim 16, wherein the defect review selector selects random defects likely to be nuisance defects by comparing the CF value for the individual random defects to a predefined threshold.

18. The computer-implemented system of claim 16, wherein the criticality factor calculator calculates the CF value by:

identifying an open area, wherein the open area is a total area of all locations inside a design layout area to cause an open failure, and identifying a short area, wherein the short area is a total area of all locations inside the design layout to cause a short failure; and

calculating a probability of the random defect to cause an open failure and a probability of the defect to cause a short failure.

19. The computer-implemented system of claim 14, wherein the nuisance defect detector includes a defect comparator to determine which systematic defects are likely to be nuisance defects by:

comparing systematic defects assigned to a structural bin to historical data for defects of previous structural bins; and

determining whether the systematic defects assigned to the structural bin are systematic defects already known to be nuisance defects.

20. A computer-implemented apparatus comprising:

means for receiving geometric characteristics of individual defects and design data corresponding to the individual defects;

means for determining which of the individual defects are likely to be nuisance defects using the geometric characteristics and the corresponding design data; and

means for refraining from sampling the defects that are likely to be nuisance defects.

21. The computer-implemented apparatus of claim 20, wherein the means for determining which of the individual defects are likely to be nuisance defects comprises:

means for separating the individual defects into systematic defects and random defects;

means for determining which random defects are likely to be nuisance defects; and

means for determining which systematic defects are likely to be nuisance defects.

22. The computer-implemented apparatus of claim 21, wherein the means for determining which random defects are likely to be nuisance defects comprises:

means for calculating a criticality factor (CF) value for the individual random defects using the geometric characteristics and design data of the individual random defects; and

means for comparing the CF value for the individual random defects to a predefined threshold.

23. The computer-implemented apparatus of claim 21, wherein the means for determining which systematic defects are likely to be nuisance defects is by:

means for comparing systematic defects assigned to a structural bin to historical data for defects of previous structural bins; and

means for determining whether the systematic defects assigned to the structural bin are systematic defects already known to be nuisance defects based on the historical data.

24. A computer readable storage medium, comprising executable instructions which when executed on a processing system cause the processing system to perform a method comprising:

receiving geometric characteristics of individual defects and design data corresponding to the individual defects;

determining which of the individual defects are likely to be nuisance defects using the geometric characteristics and the corresponding design data; and

refraining from sampling the defects that are likely to be nuisance defects.

25. The computer readable storage medium of claim 24, wherein determining which of the individual defects are likely to be nuisance defects comprises:

separating the individual defects into systematic defects and random defects;

determining which random defects are likely to be nuisance defects; and

determining which systematic defects are likely to be nuisance defects.