DR. THOMAS CARL ANDERSON, M.D.
Osteopathic Medicine at Hospital Pkwy, Bedford, TX

7292058, Nov 6, 2007

Nov 3, 2004

10/982348

Thomas J. Anderson - Dallas TX, US

Texas Instruments Incorporated - Dallas TX

G01R 31/26

324765

According to one embodiment of the invention, a method for estimating the failure rate of semiconductor devices includes obtaining accelerated stress duration data for a plurality of semiconductor devices, determining which of the semiconductor devices fail, classifying the defects for the failed semiconductor devices, determining a distribution model for the accelerated stress duration data, determining a set of parameters for the distribution model, determining a relative proportion of each defect classification to the total number of defect classifications, determining temperature and voltage acceleration factors for each defect classification, identifying actual operating conditions for the semiconductor devices, comparing the actual operating conditions for the semiconductor device with the distribution model, and determining a defect ratio for the semiconductor devices at the actual operating conditions for a predetermined time period based on the comparison.

7494829, Feb 24, 2009

Sep 28, 2007

11/864283

Suresh Subramaniam - Richardson TX, US
Amit Vijay Nahar - Dallas TX, US
Thomas John Anderson - Dallas TX, US
Kenneth Michael Butler - Richardson TX, US
John Michael Carulli - Richardson TX, US

Texas Instruments Incorporated - Dallas TX

G01R 31/26, G06F 17/18

438 14, 438 17, 702179, 324765

Systems and methods for identification of outlier semiconductor devices using data-driven statistical characterization are described herein. At least some preferred embodiments include a method that includes identifying a plurality of sample semiconductor chips that fail a production test as a result of subjecting the plurality of sample semiconductor chips to a stress inducing process, identifying at least one correlation between variations in a first sample parameter and variations in a second sample parameter (the sample parameters associated with the plurality of sample semiconductor chips) identifying as a statistical outlier chip any of a plurality of production semiconductor chips that pass the production test and that further do not conform to a parameter constraint generated based upon the at least one correlation identified and upon data associated with at least some of the plurality of production semiconductor chips, and segregating the statistical outlier chip from the plurality of production semiconductor chip.

8126681, Feb 28, 2012

Sep 24, 2009

12/566387

Amit V Nahar - Dallas TX, US
John M Carulli - Richardson TX, US
Kenneth M Butler - Richardson TX, US
Thomas J Anderson - Dallas TX, US
Suresh Subramaniam - Richardson TX, US

Texas Instruments Incorporated - Dallas TX

G06F 19/00

702190

A method for identifying outlier semiconductor devices from a plurality of semiconductor devices includes performing at least one electrical test to obtain electrical test data including at least one test parameter, applying at least a first data transform processing methodology to the electrical test data to generate processed test data, and applying a second data transform processing methodology that is different from the first data transform processing methodology to process the processed test data. The second data transform processing methodology applies an outlier test limit to identify non-outlier devices that comprise semiconductor devices from the semiconductor devices that conform to the outlier test limit and outlier devices that do not conform to the outlier test limit. The semiconductor devices are dispositioned using the outlier identification results. At least one of the data transform processing methodologies can include statistics.