Paper
16 October 2017 Automated defect disposition with AIMS AutoAnalysis
Author Affiliations +
Abstract
The ongoing trend to smaller structures and an increasing number of high MEEF patterns in mask design makes defect disposition and repair verification more critical than ever. For AIMS™ as the standard method for defect disposition and repair verification, the requirements are getting tighter. Additionally, the efforts required for defect analysis are steadily increasing. As a result, mask manufacturers are forced to continually find methods to increase productivity and optimize the cost of defect disposition.

Smart solutions for automated defect treatment together with a high degree of tool integration play an increasing role in this challenge. With AIMS™ AutoAnalysis, which provides fully automated analysis capability of AIMS™ aerial images, ZEISS addresses this challenge. Due to direct connection and communication of AutoAnalysis with the AIMS™ system via the FAVOR® platform, the image analysis process runs in parallel to the measurement process. A high degree of automation reduces the influence of human error and provides highly reliable results.

In the following paper a study is presented demonstrating the benefits of the implementation of AutoAnalysis in the production environment at Photronics, Inc. The study was carried out by analyzing defects on pattern sets, varying from simple to very complex patterns. Furthermore, the analysis capabilities of AutoAnalysis have been compared with the capability of operators and engineers.

The performance of AutoAnalysis is presented showing significant time saving in the defect disposition process as well as an overall increase in reliability of analysis results.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guy Russell, David Jenkins, Arosha Goonesekera, Kay Dornbusch, Vahagn Sargsyan, Hendrik Zachmann, and Ute Buttgereit "Automated defect disposition with AIMS AutoAnalysis", Proc. SPIE 10451, Photomask Technology 2017, 1045113 (16 October 2017); https://doi.org/10.1117/12.2281884
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KEYWORDS
Critical dimension metrology

Image analysis

Image processing

Statistical analysis

Tolerancing

Photomasks

Manufacturing

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