Quality improvement and cost reduction using statistical outlier methods

Authors:
Amit Nahar;Kenneth M. Butler;John M. Carulli, Jr.;Charles Weinberger
Affiliations:
Texas Instruments, Dallas, TX;Texas Instruments, Dallas, TX;Texas Instruments, Dallas, TX;Texas Instruments, Dallas, TX
Venue:
ICCD'09 Proceedings of the 2009 IEEE international conference on Computer design
Year:
2009

Citing 9
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Abstract

Quality improvement and cost reduction in the overall IC manufacturing and test processes are being continuously sought. Outlier screening methods can address both of these needs. As technology scales, it has become increasingly difficult to screen outliers without excessive Type I or II errors. Hundreds of parameters are collected at wafer probe, but there lacks a systematic way of selecting outlier screens. In this paper we describe a statistical approach to both identify outliers and select beneficial screening parameters more effectively. Results on a 90nm design to reduce the burn-in fails are described.