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Optimization of Sinter Plant Operating Conditions Using Advanced Multivariate Statistics: Intelligent Data Processing

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dc.contributor.author Fernández González, Daniel
dc.contributor.author Martín Duarte, Ramón
dc.contributor.author Ruiz-Bustinza, Íñigo
dc.contributor.author Mochón, Javier
dc.contributor.author González Gasca, María del Carmen
dc.contributor.author Verdeja, Luis Felipe
dc.date.accessioned 2017-10-05T10:47:39Z
dc.date.available 2017-10-05T10:47:39Z
dc.date.issued 2016
dc.identifier.citation Fernández-González, D., Martín-Duarte, R., Ruiz-Bustinza, Í., Mochón, J., González-Gasca, C., & Verdeja, L. F. (2016). Optimization of sinter plant operating conditions using advanced multivariate statistics: Intelligent data processing. JOM, 68(8), 2089-2095. DOI: 10.1007/s11837-016-2002-2 spa
dc.identifier.issn 10474838
dc.identifier.issn 15431851
dc.identifier.uri http://hdl.handle.net/11268/6595
dc.description.abstract Blast furnace operators expect to get sinter with homogenous and regular properties (chemical and mechanical), necessary to ensure regular blast furnace operation. Blends for sintering also include several iron by-products and other wastes that are obtained in different processes inside the steelworks. Due to their source, the availability of such materials is not always consistent, but their total production should be consumed in the sintering process, to both save money and recycle wastes. The main scope of this paper is to obtain the least expensive iron ore blend for the sintering process, which will provide suitable chemical and mechanical features for the homogeneous and regular operation of the blast furnace. The systematic use of statistical tools was employed to analyze historical data, including linear and partial correlations applied to the data and fuzzy clustering based on the Sugeno Fuzzy Inference System to establish relationships among the available variables. spa
dc.description.sponsorship Spanish MICYT (MAT 2001-4435-E) spa
dc.description.sponsorship Spanish Ministry of Education, Culture and Sports via an FPU (Formación del Profesorado Universitario) spa
dc.language.iso eng spa
dc.title Optimization of Sinter Plant Operating Conditions Using Advanced Multivariate Statistics: Intelligent Data Processing spa
dc.type article spa
dc.description.impact 1.860 JCR (2016) Q1, 17/74 Metallurgy and metallurgical engineering, 5/20 Mining and mineral processing; Q2, 11/29 Mineralogy spa
dc.identifier.doi 10.1007/s11837-016-2002-2
dc.rights.accessRights closedAccess spa
dc.subject.uem Proceso de datos spa
dc.subject.uem Estadística spa
dc.subject.unesco Procesamiento de datos spa
dc.subject.unesco Estadística spa
dc.description.filiation UEM spa
dc.peerreviewed Si spa


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