METHOD AND APPARATUS FOR MONITORING OPTICAL PROXIMITY CORRECTION PERFORMANCE

• US 20090144692A1
• Filed: 11/30/2007
• Published: 06/04/2009
• Est. Priority Date: 11/30/2007
• Status: Active Application

• Current Assignee: GlobalFoundries, Inc.
• Original Assignee: GlobalFoundries, Inc.
• Inventors: Tabery, Cyrus E., CAIN, JASON P., Singh, Bhanwar, Lensing, Kevin R., Capodieci, Luigi
• Application Number:
  US11/948,151
• Publication Number:
  US 20090144692A1
• Time in Patent Office: Days
• US Class Current: 716/50
• CPC Class Codes: G03F 1/36 Masks having proximity correction features; Preparation thereof, e.g. optical proximity correction [OPC] design processes
• CPC Class Codes: G03F 1/68 Preparation processes not covered by groups G03F1/20 - G03F1/50

Abstract

A method includes specifying a plurality of optical proximity correction metrology sites on a wafer. Metrology data is collected from at least a subset of the metrology sites. Data values are predicted for the subset of the metrology sites using an optical proximity correction design model. The collected metrology data is compared to the predicted data values to generate an optical proximity correction metric. A problem condition associated with the optical proximity correction design model is identified based on the optical proximity correction metric.

Claims

1. A method, comprising:

specifying a plurality of optical proximity correction metrology sites on a wafer;

collecting metrology data from at least a subset of the metrology sites;

predicting data values for the subset of the metrology sites using an optical proximity correction design model;

comparing the collected metrology data to the predicted data values to generate an optical proximity correction metric; and

identifying a problem condition associated with the optical proximity correction design model based on the optical proximity correction metric.

2. The method of claim 1, wherein comparing the collected metrology data to the predicted data values further comprises:

determining a weighted average of the metrology data for at least each of the metrology sites in the subset; and

generating the optical proximity correction metric based on the weighted averages.

3. The method of claim 1, further comprising normalizing the metrology data with respect to a mean value associated with production metrology data collected at sites other than optical proximity correction metrology sites.

4. The method of claim 1, further comprising increasing a size of the subset responsive to identifying the problem condition.

5. The method of claim 4, further comprising:

generating the optical proximity correction metric for the increased size subset; and

identifying a fault condition associated with the optical proximity correction design model based on the optical proximity correction metric.

6. The method of claim 1, wherein the metrology data comprises dimension data.

7. The method of claim 1, further comprising:

defining a plurality of model spaces for the optical proximity correction design model;

assigning each of the metrology sites to one of the model spaces;

generating an optical proximity correction metric for each of the model spaces; and

identifying the problem condition based on the generated optical proximity correction metrics.

8. The method of claim 7, wherein each model space is associated with a particular feature type.

9. The method of claim 1, further comprising determining at least one operating recipe parameter for a photolithography tool operable to process the wafers based on the optical proximity correction metric.

10. The method of claim 9, wherein the operating recipe parameter comprises at least one of a dose parameter, a focus parameter, an illumination type parameter, a sigma parameter, and a numerical aperture parameter.

11. A method, comprising:

specifying a plurality of optical proximity correction metrology sites on a wafer;

collecting metrology data from at least a subset of the metrology sites;

comparing the collected metrology data to predicted data values for the associated metrology sites to generate an optical proximity correction metric; and

determining at least one operating recipe parameter for a photolithography tool operable to process the wafers based on the optical proximity correction metric.

12. The method of claim 11, wherein the operating recipe parameter comprises at least one of a dose parameter, a focus parameter, an illumination type parameter, a sigma parameter, and a numerical aperture parameter.

13. The method of claim 11, further comprising predicting the data values for the subset of the metrology sites using an optical proximity correction design model.

14. The method of claim 13, further comprising determining the at least one operating recipe parameter for the photolithography tool using an optical proximity correction control model.

15. The method of claim 13, further comprising:

defining a plurality of model spaces for the optical proximity correction design model;

assigning each of the metrology sites to one of the model spaces;

generating an optical proximity correction metric for each of the model spaces; and

determining the at least one operating recipe parameter for the photolithography tool on the optical proximity correction metrics.

16. The method of claim 15, wherein each model space is associated with a particular feature type.

17. The method of claim 11, wherein the metrology data comprises dimension data.

18. The method of claim 11, further comprising processing subsequent wafers using the determined at least one operating recipe parameter.

19. A system, comprising:

a metrology tool operable to collect metrology data from at least a subset of optical proximity correction metrology sites specified on a wafer; and

an optical proximity correction monitor operable to predict data values for the subset of the metrology sites using an optical proximity correction design model, compare the collected metrology data to the predicted data values to generate an optical proximity correction metric, and identify a problem condition associated with the optical proximity correction design model based on the optical proximity correction metric.

20. The system of claim 19, wherein the optical proximity correction monitor is operable to increase a size of the subset responsive to identifying the problem condition, generate the optical proximity correction metric for the increased size subset, and identify a fault condition associated with the optical proximity correction design model based on the optical proximity correction metric.

21. A system, comprising:

a photolithography tool operable to pattern wafers for forming features thereon;

a metrology tool operable to collect metrology data from at least a subset of optical proximity correction metrology sites specified on at least one wafer; and

a controller operable to compare the collected metrology data to predicted data values for the associated metrology sites to generate an optical proximity correction metric and determine at least one operating recipe parameter for the photolithography tool based on the optical proximity correction metric.

22. The system of claim 21, wherein the operating recipe parameter comprises at least one of a dose parameter, a focus parameter, an illumination type parameter, a sigma parameter, and a numerical aperture parameter.

23. The system of claim 21, wherein the controller is operable to receive the predicted data values for the subset of the metrology sites as generated by an optical proximity correction design model and determine the at least one operating recipe parameter for the photolithography tool using an optical proximity correction control model.