An integrated spatial signature analysis and automatic defect classification system
An integrated Spatial Signature Analysis (SSA) and automatic defect classification (ADC) system for improved automatic semiconductor wafer manufacturing characterization is presented. Both concepts of SSA and ADC methodologies are reviewed and then the benefits of an integrated system are described, namely, focused ADC and signature-level sampling. Focused ADC involves the use of SSA information on a defect signature to reduce the number of possible classes that an ADC system must consider, thus improving the ADC system performance. Signature-level sampling improved the ADC system throughput and accuracy by intelligently sampling defects within a given spatial signature for subsequent off-line, high-resolution ADC. A complete example of wafermap characterization via an integrated SSA/ADC system is presented where a wafer with 3274 defects is completely characterized by revisiting only 25 defects on an off-line ADC review station. 13 refs., 7 figs.
- Research Organization:
- Oak Ridge National Lab., TN (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC05-96OR22464
- OSTI ID:
- 519099
- Report Number(s):
- CONF-9706148--1; ON: DE97007759
- Country of Publication:
- United States
- Language:
- English
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