A method to determinate the thickness control parameters in cold rolling process through predictive model via neural networks

L. E. Zárate

doi:10.1590/s1678-58782005000400003

A method to determinate the thickness control parameters in cold rolling process through predictive model via neural networks

Journal of the Brazilian Society of Mechanical Sciences and Engineering ◽

10.1590/s1678-58782005000400003 ◽

2005 ◽

Vol 27 (4) ◽

pp. 357-363 ◽

Cited By ~ 5

Author(s):

L. E. Zárate

Keyword(s):

Neural Networks ◽

Cold Rolling ◽

Predictive Model ◽

Rolling Process ◽

Control Parameters ◽

Thickness Control

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A predictive thickness control structure and decision about the better control parameter for the cold rolling process through sensitivity factors via neural networks

Proceedings of the 2005 IEEE Midnight-Summer Workshop on Soft Computing in Industrial Applications, 2005. SMCia/05. ◽

10.1109/smcia.2005.1466941 ◽

2005 ◽

Author(s):

L.E. Zarate

Keyword(s):

Neural Networks ◽

Cold Rolling ◽

Control Parameter ◽

Control Structure ◽

Rolling Process ◽

Thickness Control ◽

Sensitivity Factors

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Determination of the thickness control parameters of the rolling process through the sensitivity method, using neural networks

Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IPMM'99 (Cat. No.99EX296) ◽

10.1109/ipmm.1999.792535 ◽

1999 ◽

Cited By ~ 2

Author(s):

L.E. Zarate ◽

H. Helman

Keyword(s):

Neural Networks ◽

Rolling Process ◽

Control Parameters ◽

Thickness Control ◽

Sensitivity Method

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Predictive model for the cold rolling process through sensitivity factors via neural networks

Journal of the Brazilian Society of Mechanical Sciences and Engineering ◽

10.1590/s1678-58782006000100013 ◽

2006 ◽

Vol 28 (1) ◽

Cited By ~ 1

Author(s):

Luis E. Zárate

Keyword(s):

Neural Networks ◽

Cold Rolling ◽

Predictive Model ◽

Rolling Process ◽

Sensitivity Factors

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Application of convolutional neural networks for prediction of strip flatness in tandem cold rolling process

Journal of Manufacturing Processes ◽

10.1016/j.jmapro.2021.05.062 ◽

2021 ◽

Vol 68 ◽

pp. 512-522

Author(s):

Yu Wang ◽

Changsheng Li ◽

Lianggui Peng ◽

Ruida An ◽

Xin Jin

Keyword(s):

Neural Networks ◽

Cold Rolling ◽

Convolutional Neural Networks ◽

Rolling Process ◽

Strip Flatness ◽

Tandem Cold Rolling

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Neural networks and fuzzy rules based control for cold rolling process via sensitivity factors

IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243) ◽

10.1109/iecon.2001.976455 ◽

2002 ◽

Cited By ~ 2

Author(s):

L.E. Zarate ◽

F.R. Bittencout

Keyword(s):

Neural Networks ◽

Cold Rolling ◽

Rolling Process ◽

Fuzzy Rules ◽

Sensitivity Factors

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Representation and control of the cold rolling process through artificial neural networks via sensitivity factors

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2007.06.063 ◽

2008 ◽

Vol 197 (1-3) ◽

pp. 344-362 ◽

Cited By ~ 18

Author(s):

Luis E. Zárate ◽

Fabrício R. Bittencout

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Cold Rolling ◽

Rolling Process ◽

Sensitivity Factors ◽

Artificial Neural ◽

And Control

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Neural Networks Applied to Adjustment and Combination of the Control Actions for the Cold Rolling Process

2007 International Joint Conference on Neural Networks ◽

10.1109/ijcnn.2007.4371034 ◽

2007 ◽

Author(s):

Luis E. Zarate ◽

Fabricio R. Bittencout

Keyword(s):

Neural Networks ◽

Cold Rolling ◽

Rolling Process ◽

Control Actions

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Neural networks to improve mathematical model adaptation in the flat steel cold rolling process

The 2010 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2010.5596794 ◽

2010 ◽

Author(s):

Antonio Luiz dos Santos Filho ◽

Francisco Javier Ramirez-Fernandez

Keyword(s):

Neural Networks ◽

Mathematical Model ◽

Cold Rolling ◽

Rolling Process ◽

Model Adaptation ◽

Flat Steel

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Dynamic characteristics of cold rolling mill and strip based on flatness and thickness control in rolling process

Journal of Central South University ◽

10.1007/s11771-014-1975-7 ◽

2014 ◽

Vol 21 (2) ◽

pp. 567-576 ◽

Cited By ~ 13

Author(s):

Jian-liang Sun ◽

Yan Peng ◽

Hong-min Liu

Keyword(s):

Cold Rolling ◽

Dynamic Characteristics ◽

Rolling Mill ◽

Rolling Process ◽

Cold Rolling Mill ◽

Thickness Control

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Predictive model for thick steel laser cutting quality using artificial neural networks

International Congress on Applications of Lasers & Electro-Optics ◽

10.2351/1.5061187 ◽

2007 ◽

Author(s):

M. Sundar ◽

A. K. Nath ◽

D. K. Bandyopadhyay ◽

S. P. Chaudhuri ◽

P. K. Dey ◽

...

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Predictive Model ◽

Laser Cutting ◽

Thick Steel ◽

Artificial Neural

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