Methods and apparatus for hybrid outlier detection

• US 8,606,536 B2
• Filed: 10/15/2009
• Issued: 12/10/2013
• Est. Priority Date: 05/24/2002
• Status: Active Grant

• Current Assignee: In-Depth Test LLC (Acacia Research Corporation)
• Original Assignee: Test Acuity Solutions, Inc (Boston Semi Equipment, LLC)
• Inventors: Miguelanez, Emilio, LaBonte, Greg I.
• Primary Examiner(s): Huynh, Phuong
• Application Number:
  US12/579,634
• Publication Number:
  US 20100036637A1
• Time in Patent Office: 1,517 Days
• Field of Search: 702/118, 702121-123, 702182-188
• US Class Current: 702/118
• CPC Class Codes: G01R 31/2894 Aspects of quality control [QC] G01R31/31718 takes precedence; program control for QC G05B19/41875

Abstract

Methods and apparatus for data analysis according to various aspects of the present invention are configured to identify statistical outliers in test data for components, including hybrid outliers representing outliers within subsets of larger data populations. A method and apparatus according to various aspects of the present invention may operate in conjunction with a test system having a tester, such as automatic test equipment (ATE) for testing semiconductors.

Claims

1. A test data analysis system for analyzing test data for multiple components fabricated on a wafer, comprising:

a memory configured to store the test data; and

a hybrid outlier system having access to the memory and configured to, for each of a plurality of test data for each of a plurality of components;

select a central component from the plurality of components;

identify a plurality of local components in a local area near the central component;

determine a derived value of the test data for the plurality of local components;

compare the test data for the central component to the derived value for the plurality of local components; and

identify whether the test data for the central component represents a hybrid outlier according to the comparison of the test data for the central component to the derived value for the plurality of local components.

2. A test data analysis system according to claim 1, wherein the hybrid outlier system is configured to normalize the test data for the central component and the local components.

3. A test data analysis system according to claim 2, wherein the hybrid outlier system is configured to compare the test data for the central component to the derived value for the plurality of test components by comparing the normalized test data for the central component to the derived value for the plurality of test components.

4. A test data analysis system according to claim 2, wherein the test data comprises test data generated using multi-site testing, and wherein the hybrid outlier system is configured to normalize the test data for the central component and the local components to counter an inconsistency induced by the multi-site testing.

5. A test data analysis system according to claim 1, further comprising an outlier identification system configured to remove a global outlier from the test data before identifying whether the test data for the central component represents the hybrid outlier.

6. A test data analysis system according to claim 1, wherein the derived value comprises an average value for the plurality of local components.

7. A test data analysis system according to claim 1, wherein the hybrid outlier system is configured to identify the plurality of local components according to a pattern, and wherein the hybrid outlier system is configured to automatically increase a size of the pattern until a minimum number of local components satisfying a selected criterion are within the pattern.

8. A computer-implemented method for analyzing test data for multiple components fabricated on a wafer, comprising:

selecting a central component from the multiple components;

identifying a plurality of local components in a local area near the central component;

determining a derived value of the test data for the plurality of local components via a computer;

comparing the test data for the central component to the derived value for the plurality of local components; and

identifying whether the test data for the central component represents a hybrid outlier according to the comparison of the test data for the central component to the derived value for the plurality of local components.

9. A computer-implemented method for analyzing test data according to claim 8, further comprising normalizing the test data for the central component and the local components on the wafer.

10. A computer-implemented method for analyzing test data according to claim 9, wherein comparing the test data for the central component to the derived value for the plurality of test components comprises comparing the normalized test data for the central component to the derived value for the plurality of test components.

11. A computer-implemented method for analyzing test data according to claim 9, wherein:

the test data comprises test data generated using multi-site testing;

and normalizing the test data for the central component and the local components comprises normalizing the test data to counter an inconsistency induced by the multi-site testing.

12. A computer-implemented method for analyzing test data according to claim 8, wherein the derived value comprises an average value for the plurality of local components.

13. A computer-implemented method for analyzing test data according to claim 8, further comprising removing a global outlier from the test data before identifying whether the test data for the central component represents the hybrid outlier.

14. A computer-implemented method for analyzing test data according to claim 8, wherein identifying the plurality of local components comprises identifying the plurality of local components according to a pattern, and further comprising automatically increasing a size of the pattern until a minimum number of local components satisfying a selected criterion are within the pattern.

15. A non-transitory computer-readable medium containing computer instructions stored therein for causing a computer processor to perform analysis on test data for components on a wafer, wherein the instructions cause the computer to:

select a central component;

identify a plurality of local components in a local area near the central component;

determine a derived value of the test data for the plurality of local components;

compare the test data for the central component to the derived value for the plurality of local components; and

identify whether the test data for the central component represents a hybrid outlier according to the comparison of the test data for the central component to the derived value for the plurality of local components.

16. A non-transitory computer-readable medium according to claim 15, wherein the instructions further cause the computer to normalize the test data for the central component and the local components on the wafer.

17. A non-transitory computer-readable medium according to claim 16, wherein the instructions further cause the computer to compare the test data for the central component to the derived value for the plurality of test components by comparing the normalized test data for the central component to the derived value for the plurality of test components.

18. A non-transitory computer-readable medium according to claim 16, wherein the test data comprises test data generated using multi-site testing, and wherein the hybrid outlier system is configured to normalize the test data for the central component and the local components to counter an inconsistency induced by the multi-site testing.

19. A non-transitory computer-readable medium according to claim 15, wherein the derived value comprises an average value for the plurality of local components.

20. A non-transitory computer-readable medium according to claim 15, wherein the instructions further cause the computer to remove a global outlier from the test data before identifying whether the test data for the central component represents the hybrid outlier.

21. A non-transitory computer-readable medium according to claim 15, wherein the plurality of local components are selected according to a pattern, and wherein the instructions cause the computer to automatically increase a size of the pattern until a minimum number of local components satisfying a selected criterion are within the pattern.