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Proceedings Paper

Process monitoring for micro-fabrication based on machine vision
Author(s): Guohua Gao; Hongguang Zhang; Jing Zhao; Yu Zhu; Guanghong Duan
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Paper Abstract

Most of Micro-fabrication technologies are one complex process. The final machining precision and forming quality of the 3D microstructures are decided not only by the movement and control performance of the machining system, but also by various outside condition factors. Through real-time monitoring the machining process and eliminating the technical error, the fabricating successful rate and completing rate will be improved. In this paper, one process monitoring system based on Machine Vision is presented to be used in one Femtosecond laser micro-fabrication system. According to the technic characteristic, point to point and layer to layer molding, two monitoring strategies are put forwarded respectively to different machining process. Single cell point image is used to judge the laser solidified result through the Support Vector Machine and the machining precision can be promised. The layer image is used to be compared with the design locus and the forming quality of the 3D microstructure can be gained. Whole vision monitoring system is built with the Virtual Instrument development condition, Labview. The image obtaining and process are both realized by software, this decreases the system developing cost. The strategy of the vision monitoring system is also applicable for other micro-fabrication system.

Paper Details

Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71300W (31 December 2008); doi: 10.1117/12.819569
Show Author Affiliations
Guohua Gao, Beijing Univ. of Technology (China)
Hongguang Zhang, Beijing Univ. of Technology (China)
Jing Zhao, Beijing Univ. of Technology (China)
Yu Zhu, Tsinghua Univ. (China)
Guanghong Duan, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

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