5 April 2012 Automated Heuristic Defect Classification (AHDC) for haze-induced defect growth management and mask requalification
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Abstract
This article presents results from a heuristic automated defect classification algorithm for reticle inspection that mimics the classification rules. AHDC does not require CAD data, thus it can be rapidly deployed in a high volume production environment without the need for extensive design data management. To ensure classification consistency a software framework tracks every defect in repeated inspections. Through its various image based derived metrics it is shown that such a system manages and tracks repeated defects in applications such as haze induced defect growth.
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Saghir Munir, Gul Qidwai, "Automated Heuristic Defect Classification (AHDC) for haze-induced defect growth management and mask requalification", Proc. SPIE 8324, Metrology, Inspection, and Process Control for Microlithography XXVI, 83243C (5 April 2012); doi: 10.1117/12.924329; https://doi.org/10.1117/12.924329
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