10 May 2005 Repair simulation with image processing and artificial intelligence
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Defect-free mask is a dream of mask makers. Repair technology [1] that removes defects on Att. PSM is getting more attentions than ever. Therefore the fast and precise verification of repaired results is highly required. Most confirmation methods are carried out by using the inspection system because it is faster than AIMS to verify the repaired results. However, the accuracy of the verification using the inspection system cannot be compared to it with AIMS in the view of printability. In this paper, the results of optical simulation using top-down repair image are compared with those of AIMS for rapid confirmation of repaired results with competitive accuracy. Also, neural network which can compute the complex non-linear relationships easily are used to increase the accuracy of repair simulation.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yo-Han Choi, Yo-Han Choi, Moon-Kyu Sung, Moon-Kyu Sung, Sang-Hyun Lee, Sang-Hyun Lee, Ji-Hyung Lee, Ji-Hyung Lee, Jin-Hong Park, Jin-Hong Park, Ji-Hyun Choi, Ji-Hyun Choi, Seong-Yong Moon, Seong-Yong Moon, Sung-Woon Choi, Sung-Woon Choi, Woo-Sung Han, Woo-Sung Han, } "Repair simulation with image processing and artificial intelligence", Proc. SPIE 5752, Metrology, Inspection, and Process Control for Microlithography XIX, (10 May 2005); doi: 10.1117/12.599369; https://doi.org/10.1117/12.599369


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