Adaptive virtual metrology for semiconductor chemical mechanical planarization process using GMDH-type polynomial neural networks-Reference-Cited by-同舟云学术

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Adaptive virtual metrology for semiconductor chemical mechanical planarization process using GMDH-type polynomial neural networks

Published:2018-02 Issue: Volume:62 Page:44-54
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Jia Xiaodong,Di Yuan,Feng Jianshe,Yang Qibo,Dai Honghao,Lee Jay

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modelling and Simulation,Control and Systems Engineering

Reference59 articles.

1. A review of production planning and scheduling models in the semiconductor industry part I: system characteristics, performance evaluation and production planning;Uzsoy;IIE Trans.,1992

2. Exponentially weighted moving average-based procedure with adaptive thresholding for monitoring nonlinear profiles: monitoring of plasma etch process in semiconductor manufacturing;Jeong;Expert Syst. Appl.,2013

3. A data mining approach considering missing values for the optimization of semiconductor-manufacturing processes;Kwak;Expert Syst. Appl.,2012

4. A novel design of wafer yield model for semiconductor using a GMDH polynomial and principal component analysis;Lin;Expert Syst. Appl.,2012

5. Application of locally weighted partial least squares to design of semiconductor virtual metrology;Hirai,2014

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