DocumentCode :
3064054
Title :
Sampling methodology for SEM-based defect classification: risk, cost, and benefit analysis
Author :
Akella, Ram ; Lin, Chih-Hung ; Chitturi, Prasanna
Author_Institution :
Stanford Univ., CA, USA
fYear :
1998
fDate :
1998
Firstpage :
319
Lastpage :
323
Abstract :
The current paper analyzes the relative merits of optical and SEM-based defect classification systems, the needs and costs associated with these systems, and the factors limiting the usability of these systems. In particular, we consider the impact of throughput rate and classification accuracy, on excursion detection and the resulting economic benefits. The paper includes a discussion of these models and a comparison is made to obtain the maximum benefits from existing optical and SEM review and classification methodologies. Scenarios for 0.25 micron fabs are used to indicate the procedures and policies that are the most effective from a fab economic perspective
Keywords :
cost-benefit analysis; flaw detection; inspection; integrated circuit economics; integrated circuit modelling; integrated circuit yield; process monitoring; sampling methods; scanning electron microscopy; statistical process control; 0.25 micron; SEM-based defect classification; automated process; classification accuracy; classification methodology; economic benefits; excursion detection; in-line monitoring; optical-based defect classification; review methodology; risk/cost/benefit analysis; sampling methodology; semiconductor manufacturing; throughput rate; yield management; Cost benefit analysis; Inspection; Optical materials; Risk analysis; Sampling methods; Semiconductor device manufacture; Semiconductor device modeling; Technology management; Throughput; Usability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Solid-State and Integrated Circuit Technology, 1998. Proceedings. 1998 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4306-9
Type :
conf
DOI :
10.1109/ICSICT.1998.785885
Filename :
785885
Link To Document :
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