Paper
20 May 2006 Automated evaluation of AIMS images: an approach to minimize evaluation variability
Arndt C. Dürr, Martin Arndt, Jan Fiebig, Samuel Weiss
Author Affiliations +
Abstract
Defect disposition and qualification with stepper simulating AIMS tools on advanced masks of the 90nm node and below is key to match the customer's expectations for "defect free" masks, i.e. masks containing only non-printing design variations. The recently available AIMS tools allow for a large degree of automated measurements enhancing the throughput of masks and hence reducing cycle time - up to 50 images can be recorded per hour. However, this amount of data still has to be evaluated by hand which is not only time-consuming but also error prone and exhibits a variability depending on the person doing the evaluation which adds to the tool intrinsic variability and decreases the reliability of the evaluation. In this paper we present the results of an MatLAB based algorithm which automatically evaluates AIMS images. We investigate its capabilities regarding throughput, reliability and matching with handmade evaluation for a large variety of dark and clear defects and discuss the limitations of an automated AIMS evaluation algorithm.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arndt C. Dürr, Martin Arndt, Jan Fiebig, and Samuel Weiss "Automated evaluation of AIMS images: an approach to minimize evaluation variability", Proc. SPIE 6283, Photomask and Next-Generation Lithography Mask Technology XIII, 62832A (20 May 2006); https://doi.org/10.1117/12.681781
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Photomasks

Image processing

Reliability

Image analysis

Environmental sensing

Algorithm development

Image quality

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