Yield-oriented computer-aided defect diagnosis

Author

Khare, Jitendra B. ; Maly, Wojciech ; Griep, Susanne ; Schmitt-Landsiedel, Doris

Author_Institution

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

8

Issue

2

fYear

1995

fDate

5/1/1995 12:00:00 AM

Firstpage

195

Lastpage

206

Abstract

Any good yield-oriented defect strategy must have two main components-(a) the ability to perform rapid defect diagnosis for yield learning, and (b) the ability to efficiently extract defect parameters from the manufacturing line. In this work, an inductive fault analysis (IFA)-based defect methodology is investigated to see if it meets the above requirements. Using an SRAM test vehicle as an example, the research analyzes whether computer-generated mappings between defect types and tester fail data can provide sufficient resolution for both, defect diagnosis and defect parameter characterization

Keywords

SRAM chips; failure analysis; fault diagnosis; integrated circuit testing; integrated circuit yield; semiconductor process modelling; SRAM test vehicle; computer-aided defect diagnosis; computer-generated mappings; defect methodology; defect parameters; fail data; inductive fault analysis; manufacturing line; yield learning; Data mining; Dictionaries; Fabrication; Failure analysis; Logic arrays; Manufacturing; Random access memory; Semiconductor device manufacture; Testing; Vehicles;

fLanguage

English

Journal_Title

Semiconductor Manufacturing, IEEE Transactions on

Publisher

ieee

ISSN

0894-6507

Type

jour

DOI

10.1109/66.382283

Filename

382283