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Proceedings Paper

SEM-based automatic defect classification (ADC)
Author(s): Fred Lakhani; Wanda Tomlinson
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Paper Abstract

Automatic defect classification (ADC) on the optical defect detection and review tools have found increasing acceptance in the cleanroom for defect reduction during all phases of yield learning (process R&D, yield ramp and mature production). However at 180 nm technology node, the optical tools are unable to classify the smaller defects of interest. SEM based ADC tools provide this capability through high resolution imaging and classification. This paper will provide an overview of past and future yield learning trends and challenges, role of ADC in the yield learning process and a detailed review of the SEM based ADC tool evaluation project conducted at SEMATECH during 1997/1998 which yielded the following beta results at a SEMATECH member company fab.

Paper Details

Date Published: 27 August 1999
PDF: 8 pages
Proc. SPIE 3884, In-Line Methods and Monitors for Process and Yield Improvement, (27 August 1999); doi: 10.1117/12.361345
Show Author Affiliations
Fred Lakhani, SEMATECH (United States)
Wanda Tomlinson, IBM Corp. (United States)


Published in SPIE Proceedings Vol. 3884:
In-Line Methods and Monitors for Process and Yield Improvement
Sergio A. Ajuria; Jerome F. Jakubczak, Editor(s)

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