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Proceedings Paper

Repair simulation with image processing and artificial intelligence
Author(s): Yo-Han Choi; Moon-Kyu Sung; Sang-Hyun Lee; Ji-Hyung Lee; Jin-Hong Park; Ji-Hyun Choi; Seong-Yong Moon; Sung-Woon Choi; Woo-Sung Han
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Paper Abstract

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.

Paper Details

Date Published: 10 May 2005
PDF: 7 pages
Proc. SPIE 5752, Metrology, Inspection, and Process Control for Microlithography XIX, (10 May 2005); doi: 10.1117/12.599369
Show Author Affiliations
Yo-Han Choi, Samsung Electronics Co., Ltd. (South Korea)
Moon-Kyu Sung, Samsung Electronics Co., Ltd. (South Korea)
Sang-Hyun Lee, Samsung Electronics Co., Ltd. (South Korea)
Ji-Hyung Lee, SungKyunKwan Univ. (South Korea)
Jin-Hong Park, SAMSUNG Electronics Co., Ltd. (South Korea)
Ji-Hyun Choi, Samsung Electronics Co., Ltd. (South Korea)
Seong-Yong Moon, Samsung Electronics Co., Ltd. (South Korea)
Sung-Woon Choi, Samsung Electronics Co., Ltd. (South Korea)
Woo-Sung Han, Samsung Electronics Co., Ltd. (South Korea)


Published in SPIE Proceedings Vol. 5752:
Metrology, Inspection, and Process Control for Microlithography XIX
Richard M. Silver, Editor(s)

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