A neural network-based preset generation tool for a steel tandem cold mill


Autoria(s): dos Santos Filho, Antonio Luiz; Ramirez-Fernandez, Francisco Javier
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/03/2010

Resumo

This paper traces the development of a software tool, based oil a combination of artificial neural networks (ANN) and a few process equations. aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as ail option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based oil a lookup table). which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this land of process. The text characterizes the problem, relates the investigated options to solve it. justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results. (C) 2009 Elsevier Ltd. All rights reserved

Formato

169-176

Identificador

http://dx.doi.org/10.1016/j.engappai.2009.10.004

Engineering Applications of Artificial Intelligence. Oxford: Pergamon-Elsevier B.V. Ltd, v. 23, n. 2, p. 169-176, 2010.

0952-1976

http://hdl.handle.net/11449/40220

10.1016/j.engappai.2009.10.004

WOS:000275785300004

Idioma(s)

eng

Publicador

Pergamon-Elsevier B.V. Ltd

Relação

Engineering Applications of Artificial Intelligence

Direitos

closedAccess

Palavras-Chave #Intelligent automation #Artificial neural networks #Cold rolling #Mill setup
Tipo

info:eu-repo/semantics/article