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Proceedings Paper

Application of BP-neural networks in the FOCAL technique
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Paper Abstract

FOCAL is an on-line measurement technique of the imaging parameters of a lithographic tool with high accuracy. These parameters include field curvature, astigmatism, best focus and image tilt. They can be acquired by the least-square algorithm from the alignment positions of the special marks on the exposed wafer. But the algorithm has some intrinsic limits which may lead to a failure of the curve fitting. This will influence the measurement accuracy of the imaging parameters obtained by FOCAL. Therefore, a more reliable algorithm for the FOCAL technique is needed. In this paper, the feed-forward back-propagation artificial neural network algorithm is introduced in the FOCAL technique, and the FOCAL technique based on BP ANN is proposed. The effects of the parameters, such as the number of neurons on the hidden-layer, the number of training epochs, on the measurement accuracy are analyzed in detail. It is proved that the FOCAL technique based on BP-ANN is more reliable and it is a better choice for measurement of the imaging parameters.

Paper Details

Date Published: 27 January 2005
PDF: 7 pages
Proc. SPIE 5645, Advanced Microlithography Technologies, (27 January 2005); doi: 10.1117/12.573822
Show Author Affiliations
Weijie Shi, Shanghai Institute of Optics and Fine Mechanics, CAS (China)
Xiangzhao Wang, Shanghai Institute of Optics and Fine Mechanics, CAS (China)
Dongqing Zhang, Shanghai Institute of Optics and Fine Mechanics, CAS (China)
Fan Wang, Shanghai Institute of Optics and Fine Mechanics, CAS (China)
Mingying Ma, Shanghai Institute of Optics and Fine Mechanics, CAS (China)


Published in SPIE Proceedings Vol. 5645:
Advanced Microlithography Technologies
Yangyuan Wang; Jun-en Yao; Christopher J. Progler, Editor(s)

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