System, method and computer program product for systematic and stochastic characterization of pattern defects identified from a semiconductor wafer

• US 10,262,408 B2
• Filed: 08/22/2017
• Issued: 04/16/2019
• Est. Priority Date: 04/12/2017
• Status: Active Grant

• Current Assignee: KLA-Tencor Corporation (KLA Corporation)
• Original Assignee: KLA-Tencor Corporation (KLA Corporation)
• Inventors: Park, Allen, Preil, Moshe, Cross, Andrew James
• Primary Examiner(s): Dunphy, David F
• Application Number:
  US15/683,631
• Publication Number:
  US 20180300870A1
• Time in Patent Office: 602 Days
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/0006 using a design-rule based approach
• CPC Class Codes: G06V 2201/06 Recognition of objects for industrial automation

Abstract

A system, method, and computer program product are provided for systematic and stochastic characterization of pattern defects identified from a fabricated component. In use, a plurality of pattern defects detected from a fabricated component are identified. Additionally, attributes of each of the pattern defects are analyzed, based on predefined criteria. Further, a first set of pattern defects of the plurality of pattern defects are determined, from the analysis, to be systematic pattern defects, and a second set of pattern defects of the plurality of pattern defects are determined, from the analysis, to be stochastic pattern defects. Moreover, a first action is performed for the determined systematic pattern defects and a second action is performed for the determined stochastic pattern defects.

Claims

1. A non-transitory computer readable medium storing a computer program product having code executable by a processor to perform a method comprising:

identifying a plurality of pattern defects detected from a fabricated component;

analyzing attributes of each of the pattern defects, based on predefined criteria;

determining, from the analysis, a first set of pattern defects of the plurality of pattern defects to be systematic pattern defects and a second set of pattern defects of the plurality of pattern defects to be stochastic pattern defects;

performing a first action for the determined systematic pattern defects; and

performing a second action for the determined stochastic pattern defects.

2. The non-transitory computer readable medium of claim 1, wherein the fabricated component is a die on a semiconductor wafer.

3. The non-transitory computer readable medium of claim 1, wherein the fabricated component is constructed using extreme ultraviolet lithography (EUV).

4. The non-transitory computer readable medium of claim 1, wherein the plurality of pattern defects is identified by:

receiving an indication of a plurality of defects detected from the fabricated component,

grouping the plurality of defects by pattern type, wherein each group represents a different pattern defect of the plurality of pattern defects.

5. The non-transitory computer readable medium of claim 4, wherein the indication of the plurality of defects detected from the fabricated component is received from an inspection system that detected the plurality of defects from the fabricated component.

6. The non-transitory computer readable medium of claim 4, further comprising collecting the attributes of each of the pattern defects from the plurality of defects.

7. The non-transitory computer readable medium of claim 1, wherein the attributes include a frequency of failure, location distribution, and a focus/exposure or other modulated condition.

8. The non-transitory computer readable medium of claim 1, wherein the predefined criteria includes a first criterion associated with a distribution of locations of defects within a pattern specific to the pattern defect.

9. The non-transitory computer readable medium of claim 8, wherein the first criterion uses defect location accuracy (DLA) of a system that detected the defects as a threshold.

10. The non-transitory computer readable medium of claim 8, wherein the predefined criteria includes a second criterion associated with a frequency of defects within the pattern specific to the pattern defect.

11. The non-transitory computer readable medium of claim 10, wherein the frequency of defects is at least one of:

determined for a particular modulation setting,

determined across different modulation settings,

determined across a wafer that includes the fabricated component, and

determined across multiple repeating wafers that include the fabricated component.

12. The non-transitory computer readable medium of claim 1, wherein analyzing the attributes of each of the pattern defects, based on predefined criteria, includes binning defects associated with the pattern defect according to the predefined criteria.

13. The non-transitory computer readable medium of claim 1, wherein determining, from the analysis, the first set of pattern defects of the plurality of pattern defects to be systematic pattern defects and the second set of pattern defects of the plurality of pattern defects to be stochastic pattern defects includes, for each of the pattern defects:

applying at least one predefined rule to a result of the analysis to determine whether the pattern defect is a systematic pattern defect or a stochastic pattern defect.

14. The non-transitory computer readable medium of claim 1, wherein each of the stochastic pattern defects is a location independent pattern defect.

15. The non-transitory computer readable medium of claim 1, wherein the first action is, at least in part, different from the second action.

16. The non-transitory computer readable medium of claim 1, wherein the first action includes optimizing a pattern associated with each of the systematic pattern defects.

17. The non-transitory computer readable medium of claim 1, wherein the second action includes optimizing modulations for the pattern associated with each of the stochastic pattern defects.

18. A method comprising:

identifying a plurality of pattern defects detected from a fabricated component;

analyzing attributes of each of the pattern defects, based on predefined criteria;

determining, from the analysis, a first set of pattern defects of the plurality of pattern defects to be systematic pattern defects and a second set of pattern defects of the plurality of pattern defects to be stochastic pattern defects;

performing a first action for the determined systematic pattern defects; and

performing a second action for the determined stochastic pattern defects.

19. A system, comprising:

a computer processor for;

identifying a plurality of pattern defects detected from a fabricated component;

analyzing attributes of each of the pattern defects, based on predefined criteria;

determining, from the analysis, a first set of pattern defects of the plurality of pattern defects to be systematic pattern defects and a second set of pattern defects of the plurality of pattern defects to be stochastic pattern defects;

performing a first action for the determined systematic pattern defects; and

performing a second action for the determined stochastic pattern defects.