KEYWORDS: Photomasks, Manufacturing, Binary data, Process engineering, Picosecond phenomena, Semiconductors, Data communications, Data mining, Information technology, Databases
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.
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