IP Library Granted Patent US 8,606,536
Granted Patent B2
US 8,606,536 · App. 12/579,634 · Granted Dec 10, 2013

Methods and apparatus for hybrid outlier detection

Inventors: Emilio Miguelanez (Edinburgh, GB); Greg I. LaBonte (Phoenix, AZ)
Assignee: Test Acuity Solutions, Inc.
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Quick Facts
Patent No.
US 8,606,536
App. No.
12/579,634
Granted
Dec 10, 2013
Kind
B2
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 (39)

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.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 30, 2014
From: ACACIA RESEARCH GROUP LLC
To: IN-DEPTH TEST LLC
Reel/Frame 032089/0907 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 28, 2014
From: TEST ACUITY SOLUTIONS, INC.
To: ACACIA RESEARCH GROUP LLC
Reel/Frame 032067/0660 →
CHANGE OF NAME Recorded Sep 18, 2012
From: TEST ADVANTAGE, INC.
To: TEST ACUITY SOLUTIONS, INC.
Reel/Frame 029002/0009 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 15, 2009
From: MIGUELANEZ, EMILIO; LABONTE, GREG
To: TEST ADVANTAGE, INC.
Reel/Frame 023376/0212 →
Continuity (8)
Continuation 11535851 · Sep 27, 2006
Continuation In Part 11134843 · May 20, 2005
Continuation In Part 12579634
Continuation In Part 10817750 · Apr 2, 2004
Continuation In Part 10730388 · Dec 7, 2003
Continuation In Part 10367355 · Feb 14, 2003
Continuation In Part 10154627 · May 24, 2002
Related Publication 20100036637A1 · Feb 11, 2010