Preset generation for a steel tandem cold mill by means of a neural network tool

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorCOSIPA Steel Works-
Autor(es): dc.contributorSão Paulo Federal Technological Education Center-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorDos Santos Filho, Antonio Luiz-
Autor(es): dc.creatorRamirez-Fernandez, Francisco Javier [UNESP]-
Data de aceite: dc.date.accessioned2022-08-04T22:01:58Z-
Data de disponibilização: dc.date.available2022-08-04T22:01:58Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2009-09-07-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/CICA.2009.4982793-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/219521-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/219521-
Descrição: dc.descriptionThis paper traces the development of a software tool, based on 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 the real-time controllers of a steel tandem cold mill. By emulating the mathematical model responsible for generating the presets under normal operational conditions, the system works as an 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 on 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 virtually all the presets needed by this kind 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. ©2009 IEEE.-
Descrição: dc.descriptionAutomation Division COSIPA Steel Works, Cubatão, SP, CEP 11573-900-
Descrição: dc.descriptionSão Paulo Federal Technological Education Center, Cubatão, SP, CEP 11533-160-
Descrição: dc.descriptionIntegrated Systems Laboratory São Paulo State University Polytechnic School, São Paulo, SP, CEP 05508-010-
Descrição: dc.descriptionIntegrated Systems Laboratory São Paulo State University Polytechnic School, São Paulo, SP, CEP 05508-010-
Formato: dc.format125-132-
Idioma: dc.languageen-
Relação: dc.relation2009 IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2009 - Proceedings-
???dc.source???: dc.sourceScopus-
Título: dc.titlePreset generation for a steel tandem cold mill by means of a neural network tool-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.