Journal
IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING
Volume 28, Issue 3, Pages 229-235Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSM.2015.2445320
Keywords
Advanced process control (APC); big data; chemical mechanical polishing (CMP); equipment engineering system (EES); fault detection and classification (FDC); machine-to-machine (M2M); non-production wafer (NPW); run-to-run (R2R); virtual metrology (VM)
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This paper describes the development and the actual utilization of fab-wide fault detection and classification (FDC) for the advanced semiconductor manufacturing using big data. In the fab-wide FDC, the collection of equipment's big data for the FDC judgment is required; hence, we developed the equipment monitoring system that handles the data in a superior method in high speed and in real time. We succeeded in stopping equipment and lots automatically when the equipment was detected as fault condition. In addition, we developed the environment that enables immediate data collection for analysis by the data aggregation and merging functions, which extracts keys correlating to yield from the equipment's parameter. Furthermore, we succeeded in development of the high-speed and high-accuracy process control system that implemented virtual metrology and the run-to-run function for the purpose to reduce process variation.
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