2010 IEEE/SEMI Advanced Semiconductor Manufacturing Conference (ASMC) 2010
DOI: 10.1109/asmc.2010.5551439
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Neural networks for advanced process control

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Cited by 4 publications
(2 citation statements)
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“…Because modern plasma etching process involves physical and chemical mechanisms, theoretical modeling based on principles is difficult to construct. In addition, it has some limit in the process control and optimization application, especially processes real-time control due to the model size and complexity [4][5][6]. So as Correspondence: hlyou@mail.xidian.edu.cn an alternative to first principle models, empirical models based on statistical design of experiment plays an important role in plasma etching control and optimization [7].…”
Section: Introductionmentioning
confidence: 99%
“…Because modern plasma etching process involves physical and chemical mechanisms, theoretical modeling based on principles is difficult to construct. In addition, it has some limit in the process control and optimization application, especially processes real-time control due to the model size and complexity [4][5][6]. So as Correspondence: hlyou@mail.xidian.edu.cn an alternative to first principle models, empirical models based on statistical design of experiment plays an important role in plasma etching control and optimization [7].…”
Section: Introductionmentioning
confidence: 99%
“…At the same time intelligent (AI) strategy based control [8][9][10][11][12][13] is now a trend as process system is becoming complex which is difficult to cope with conventional control strategy that requires accurate mathematical model. Many of them use neural network based control strategy [14][15][16][17][18]. Distributed implementation is also necessary to make the software available across several machines [19].…”
Section: Introductionmentioning
confidence: 99%