TY - JOUR
AU1 - Kubo, Tomoaki
AU2 - Ino, Tomomi
AU3 - Minami, Kazuhiro
AU4 - Minami, Masateru
AU5 - Homma, Tetsuya
AB - To maintain stable operation of semiconductor fabrication lines, statistical process control (SPC) methods are recognized to be effective. However, in semiconductor fabrication lines, there exist a huge number of process state signals to be monitored, and these signals contain both normally and non-normally distributed data. Therefore, if we try to apply SPC methods to those signals, we need one which satisfies three requirements: 1) It can deal with both normally distributed data, and non-normally distributed data, 2) It can be set up automatically, 3) It can be easily understood by engineers and technicians. In this paper, we propose a new SPC method which satisfies these three requirements at the same time. This method uses similar rules to the Shewhart chart, but can deal with non-normally distributed data by introducing “effective standard deviations”. Usefulness of this method is demonstrated by comparing false alarm ratios to that of the Shewhart chart method. In the demonstration, we use various kinds of artificially generated data, and real data observed in a chemical vapor deposition (CVD) process tool in a semiconductor fabrication line.
TI - A Statistical Process Control Method for Semiconductor Manufacturing
JF - "SICE Journal of Control, Measurement and System Integration"
DO - 10.9746/jcmsi.2.246
DA - 2009-07-01
UR - https://www.deepdyve.com/lp/taylor-francis/a-statistical-process-control-method-for-semiconductor-manufacturing-2yahZRgdaf
SP - 246
EP - 254
VL - 2
IS - 4
DP - DeepDyve
ER -