NDLI: Efficiently Performing Yield Enhancements by Identifying Dominant Physical Root Cause from Test Fail Data

Content Provider	IEEE Xplore Digital Library
Author	Sharma, M. Benware, B. Lei Ling Abercrombie, D. Lee, L. Keim, M. Huaxing Tang Wu-Tung Cheng Ting-Pu Tai Yi-Jung Chang Lin, R. Man, A.
Copyright Year	2008
Description	Author affiliation: UMC, Hsinchu (Yi-Jung Chang; Lin, R.) \|\| AMD Inc., Markham, ON (Man, A.) \|\| Mentor Graphics Corp., Wilsonville, OR (Sharma, M.; Benware, B.; Lei Ling; Abercrombie, D.; Lee, L.; Keim, M.; Huaxing Tang; Wu-Tung Cheng; Ting-Pu Tai)
Abstract	Yield enhancements in the manufacturing process today require an expensive, long and tedious physical failure analysis process to identify the root cause. In this paper we present Axiom, a new technique geared towards efficiently identifying a single dominant defect mechanism (for example in an excursion wafer) by analyzing fail data collected from the production test environment. Axiom utilizes statistical hypothesis testing in a novel way to analyze logic diagnosis data along with information on physical features in the design layout and reliably identify the dominant cause for yield loss. This new methodology was validated by applying it to a single excursion wafer produced on a 90 nm process, in which the dominant failing physical feature was correctly identified.
Starting Page	1
Ending Page	9
File Size	342251
Page Count	9
File Format	PDF
ISBN	9781424424023
ISSN	10893539
DOI	10.1109/TEST.2008.4700589
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Failure analysis Logic testing Manufacturing processes Production Data analysis Logic design History Fabrication Graphics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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