AUTOMATIC DEFECT CLASSIFICATION FOR EFFECTIVE YIELD MANAGEMENT

Authors
Citation
L. Breaux et D. Kolar, AUTOMATIC DEFECT CLASSIFICATION FOR EFFECTIVE YIELD MANAGEMENT, Solid state technology, 39(12), 1996, pp. 89
Citations number
NO
Categorie Soggetti
Engineering, Eletrical & Electronic","Physics, Applied","Physics, Condensed Matter
Journal title
ISSN journal
0038111X
Volume
39
Issue
12
Year of publication
1996
Database
ISI
SICI code
0038-111X(1996)39:12<89:ADCFEY>2.0.ZU;2-V
Abstract
Automatic defect classification (ADC) enables efficient process monito ring and enhances the diagnosis of process problems. ADC, which reduce s large volumes of defect data to concise statements of process status , may be implemented both on-line (tightly coupled to a defect detecto r) and off-line (connected to a defect review tool). Although, strictl y speaking, ADC is simply the automation of manual defect classificati on, it must be fully integrated with defect detection and analysis sys tems in order to realize the full benefit. An on-line implementation o f ADC has been in operation in a research fab at Motorola Advanced Pro ducts Research and Development Lab (APRDL) for more than a year, and h as greatly surpassed the speed and consistent accuracy capabilities of manual methods.