Enhancing fab yield with the high-reliability automation application Reticle Analyzer (RA)

In advanced manufacturing fabs, mask inspection plays a pivotal role in securing the mask quality and wafer yield. A single defect on a mask can potentially impact thousands of wafers, underscoring the criticality of accurate defect disposition. While operators can confidently classify approximately 90% of defects manually, the remaining 10% are often misclassified, directly affecting production yield. As technology nodes shrink, the adoption of advanced techniques such as Optical Proximity Correction (OPC) and Sub-Resolution Assist Feature (SRAF) in mask manufacturing poses additional challenges for operators in determining defect dispositions. Additionally, the time-consuming online defect review process hampers production efficiency. To address these challenges, STMicroelectronics has adopted an intelligent reticle disposition system known as Reticle Analyzer<sup>TM</sup> (RA). RA integrates three essential applications. First, Automated Defect Classification (ADC) ensures precise defect classification, minimizing misclassifications. By leveraging defect type, topology, and severity as outputted from advanced image processing algorithms, ADC significantly improves defect classification accuracy. Second, Defect Progressing Monitor (DPM) continuously monitors defect behavior over time. It alerts operators when defects deteriorate, enabling timely intervention to prevent yield loss. Additionally, DPM provides information on the total defect count per mask based on inspection time, allowing for early haze detection and monitoring. Third, Lithography Printability Review (LPR) assesses the potential impact of defects based on lithographic printability predictions. It simulates the aerial image on the wafer and provides comprehensive analytics to assist operators in evaluating the risks of printing. In this paper, we present the workflow of ADC, LPR, and DPM products. We discuss the qualification process during production and highlight typical production cases that showcase the advantages of RA adoption. RA’s deployment has proven invaluable in mitigating yield loss, demonstrating its indispensable role in STMicroelectronics fabs.

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Published
2024-11-20
DOI
https://doi.org/10.1117/12.3034265
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Enhancing fab yield with the high-reliability automation application Reticle Analyzer (RA)

Olivier Fagart, Vikram Tolani, Suresh Lakkapragada, Laurent Lecarpentier et al.
Industrial Vision Systems and Defect Detection
article

Enhancing fab yield with the high-reliability automation application Reticle Analyzer (RA)

Olivier Fagart, Vikram Tolani, Suresh Lakkapragada, Laurent Lecarpentier, Marco Polli, Dongmei Wu, Jing Jiao, Yuehui Wang, Zeyu Lei, Changqing Hu, Derui Li, Li Yang Xie
article en

Abstract

In advanced manufacturing fabs, mask inspection plays a pivotal role in securing the mask quality and wafer yield. A single defect on a mask can potentially impact thousands of wafers, underscoring the criticality of accurate defect disposition. While operators can confidently classify approximately 90% of defects manually, the remaining 10% are often misclassified, directly affecting production yield. As technology nodes shrink, the adoption of advanced techniques such as Optical Proximity Correction (OPC) and Sub-Resolution Assist Feature (SRAF) in mask manufacturing poses additional challenges for operators in determining defect dispositions. Additionally, the time-consuming online defect review process hampers production efficiency. To address these challenges, STMicroelectronics has adopted an intelligent reticle disposition system known as Reticle Analyzer<sup>TM</sup> (RA). RA integrates three essential applications. First, Automated Defect Classification (ADC) ensures precise defect classification, minimizing misclassifications. By leveraging defect type, topology, and severity as outputted from advanced image processing algorithms, ADC significantly improves defect classification accuracy. Second, Defect Progressing Monitor (DPM) continuously monitors defect behavior over time. It alerts operators when defects deteriorate, enabling timely intervention to prevent yield loss. Additionally, DPM provides information on the total defect count per mask based on inspection time, allowing for early haze detection and monitoring. Third, Lithography Printability Review (LPR) assesses the potential impact of defects based on lithographic printability predictions. It simulates the aerial image on the wafer and provides comprehensive analytics to assist operators in evaluating the risks of printing. In this paper, we present the workflow of ADC, LPR, and DPM products. We discuss the qualification process during production and highlight typical production cases that showcase the advantages of RA adoption. RA’s deployment has proven invaluable in mitigating yield loss, demonstrating its indispensable role in STMicroelectronics fabs.

STMicroelectronics (France) (FR)
Openalex Percentile: Top 70%
Industrial Vision Systems and Defect Detection
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