Presentation + Paper
23 October 2020 Need for comprehensive reticle data management and analytics
Author Affiliations +
Abstract
Mask-shops developing advanced reticles for use in high-volume semiconductor manufacturing generate an abundance of critical data. Most of this data is generated in the backend of the mask production line where critical dimensions (CDs), registration and defect inspections are performed, and the general emphasis of this data collection is to confirm that the mask meets certain required specifications. Some of the results gathered are also used to monitor the front-end of line processing steps like mask write, develop, etch and clean. However, with most data being disparate and staying local to the tools where they were gathered, very little gets used beyond the immediate need to disposition the mask for shipment. This extensive data, when effectively stored and analyzed, helps not only accelerate time-to-results for mask disposition but also substantially improve monitoring of the frontend process and root-cause analyses. This paper discusses requirements for an effective data management system (DMS) capable of centralizing all maskshop data. This involves not only centralizing blank and pattern defect inspection results and the associated review SEM, repair, and AIMSTM disposition data but also CD, registration and other metrology data collected. The DMS architecture needs to support connectivity and use of data from other databases in the maskshop which include production tracking, computational application results, tool and fab environment logs, etc. After centralizing the data and establishing linkage to other databases, the system needs to provide visualizations through user-interfaces and advanced analytics that are easy for use by both production and engineering. The paper introduces the new KlearViewTM mask DMS system from KLA and discusses it’s features and deployment into advanced mask manufacturing. While quintessential to maskshop operations, the DMS also serves as a bridge to reticle requalification and wafer inspection and metrology data critical to improving mask quality and qualification necessary for achieving optimal EUV lithography cost-of-ownership.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel Price, Brandon Hurt, Ryan Carlson, Ryan Gardner, Yao Zhang, Masaki Satake, Derui Li, Will Wang, Wallace Wang, Peter Liu, George Hwa, and Vikram Tolani "Need for comprehensive reticle data management and analytics", Proc. SPIE 11518, Photomask Technology 2020, 115180Q (23 October 2020); https://doi.org/10.1117/12.2573765
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KEYWORDS
Photomasks

Reticles

Analytics

Manufacturing

Inspection

Semiconducting wafers

Etching

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