US EPA

7048009 

Journal Article 

Advanced Semiconductor Manufacturing Using Big Data 

Tsuda, T; Inoue, S; Kayahara, A; Imai, SI; Tanaka, T; Sato, N; Yasuda, S; , 

2015 

Yes 

IEEE Transactions on Semiconductor Manufacturing
ISSN: 0894-6507
EISSN: 1558-2345 

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 

PISCATAWAY 

229-235 

10.1109/TSM.2015.2445320 

WOS:000359231400006 

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.