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Proceedings Paper

Automatic alignment system for optical lithography based on machine vision
Author(s): Tao Huang; Shiyuan Liu; Pengxing Yi; Tielin Shi
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Paper Abstract

This paper presents an automatic alignment system based on machine vision method. A high-speed gray pattern match algorithms is proposed based on the combination of sequential similarity detection algorithm (SSDA) and multiresolution pagoda structure algorithm (MPSA). A dynamic system calibration model suitable for the algorithm automatic alignment system is established to relate the pixel coordinate in CCD to the physical coordinate, which is based on Tsai's two-step algorithm but with the help of precise positioning of the wafer stage in X-Y directions. A lot of experiments conducted on a machine vision experimental platform confirm that the proposed technique is feasible and effective. The pattern match algorithm is demonstrated to achieve an error less than one-twentieth pixels, while the computation time is shorter than 200ms when using a large pattern image with 320×320 pixels. The absolute alignment error is illustrated to be lower than 200nm within a large field of view of 1mm×1mm after the platform is calibrated using the proposed dynamic calibration method.

Paper Details

Date Published: 18 May 2009
PDF: 7 pages
Proc. SPIE 7284, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Design, Manufacturing, and Testing of Micro- and Nano-Optical Devices and Systems, 72840I (18 May 2009); doi: 10.1117/12.832076
Show Author Affiliations
Tao Huang, Huazhong Univ. of Science and Technology (China)
Shiyuan Liu, Huazhong Univ. of Science and Technology (China)
Pengxing Yi, Huazhong Univ. of Science and Technology (China)
Tielin Shi, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7284:
4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Design, Manufacturing, and Testing of Micro- and Nano-Optical Devices and Systems
Sen Han; Masaomi Kameyama; Xiangang Luo, Editor(s)

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