A reusable framework for data-mining mask shop tools

Dan Meier

doi:10.1117/12.2065574

8 October 2014 A reusable framework for data-mining mask shop tools

Dan Meier

Proceedings Volume 9235, Photomask Technology 2014; 92351G (2014) https://doi.org/10.1117/12.2065574
Event: SPIE Photomask Technology, 2014, Monterey, California, United States

Abstract

Implementations of the Semiconductor Equipment Communications Standard (SECS) are uneven across mask shop tool sets, which often implement only tool control functionality and ignore data collection. Furthermore, data collection, if implemented at all, typically exposes only a fraction of the information available within log files created by the tool. This leaves a veritable wealth of information languishing unused in tool log files – data that could provide key insights toward improvements in tool performance, processes and utilization. This paper discusses a reusable, lightweight framework for mining data from mask shop tool log files. It details the categories of data that can be mined using this framework, as well as different actions that can be triggered based on the data. The paper also proposes a generic log file format that mask shop tool vendors can implement on any tool to facilitate tool troubleshooting and simplify automated data collection.

Citation Download Citation

Dan Meier "A reusable framework for data-mining mask shop tools", Proc. SPIE 9235, Photomask Technology 2014, 92351G (8 October 2014); https://doi.org/10.1117/12.2065574

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KEYWORDS

Photomasks

Manufacturing

Binary data

Process engineering

Picosecond phenomena

Data communications

Data mining

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