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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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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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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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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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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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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Analytical and Numerical Model of a Cold Rolling Process

10.26678/abcm.cobef2017.cof2017-1521 ◽

2017 ◽

Author(s):

João Batista de Aguiar

Keyword(s):

Numerical Model ◽

Cold Rolling ◽

Rolling Process

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Vision-based automatic detection of steel surface defects in the cold rolling process: considering the influence of industrial liquids and surface textures

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-016-9489-0 ◽

2016 ◽

Vol 90 (5-8) ◽

pp. 1665-1678 ◽

Cited By ~ 16

Author(s):

Yong Jie Zhao ◽

Yun Hui Yan ◽

Ke Chen Song

Keyword(s):

Cold Rolling ◽

Steel Surface ◽

Surface Defects ◽

Automatic Detection ◽

Rolling Process ◽

Surface Textures

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Prediction and analysis of rolling process temperature field for silicon steel in tandem cold rolling

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-021-06993-9 ◽

2021 ◽

Author(s):

Guomin Han ◽

Hongbo Li ◽

Jie Zhang ◽

Ning Kong ◽

Yujin Liu ◽

...

Keyword(s):

Temperature Field ◽

Cold Rolling ◽

Rolling Process ◽

Silicon Steel ◽

Process Temperature ◽

Tandem Cold Rolling

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