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Proceedings Paper

Log data extraction and correlation miner for lithography management system: LMS-LEC
Author(s): Eiichi Kawamura; Hidetaka Tsuda; Hidehiro Shirai; Satoru Oishi; Hideki Ina
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Paper Abstract

To attain quick turn-around time (TAT) and high yield, it is very important to remove all the problems affecting the semiconductor volume production line. For this purpose, we have used a lithography management system (LMS) as an advanced process control system. The LMS stores the critical dimension and overlay inspection results as well as the log data of the exposure tool in a relational database. This enables a quick and efficient grasp of the productivity under the present conditions and helps to identify the causes of errors. Furthermore, we developed a mining tool, called a log data extraction and correlation miner (LMS-LEC), for factor analysis on the LMS. Despite low correlation between all data, a high correlation may exist between parameters in a certain data domain. The LMS-LEC can mine such correlations easily. With this tool, we can discover previously unknown error sources that have been buried in the vast quantity of data handled by the LMS and thereby increase of the effectiveness of the exposure and inspection tool. The LMS-LEC is an extremely useful software mining tool for “equipment health” monitoring, advanced fault detection, and sophisticated data analysis.

Paper Details

Date Published: 17 May 2005
PDF: 5 pages
Proc. SPIE 5755, Data Analysis and Modeling for Process Control II, (17 May 2005); doi: 10.1117/12.594994
Show Author Affiliations
Eiichi Kawamura, Fujitsu Ltd. (Japan)
Hidetaka Tsuda, Fujitsu LSI Technology Ltd. (Japan)
Hidehiro Shirai, Fujitsu LSI Technology Ltd. (Japan)
Satoru Oishi, Canon Inc. (Japan)
Hideki Ina, Canon Inc. (Japan)


Published in SPIE Proceedings Vol. 5755:
Data Analysis and Modeling for Process Control II
Iraj Emami, Editor(s)

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