USE OF MATHEMATICAL TOOLS FOR EVALUATION OF THE QUALITY OF BLAST FURNACE COKE

1 BESTA Petr
Co-authors:
1 JANOVSKÁ Kamila 2 SEZIMA Tomáš 1 SIKOROVÁ Andrea 1 KUTÁČ Josef 1 KUTÁČ Tomáš 1 KUBICA Stanislav
Institutions:
1 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, petr.besta@vsb.cz
2 T. G. Masaryk Water Research Institute, Department of Water and Waste Management, Ostrava, Czech Republic, EU, tomas.sezima@vuv.cz
Conference:
26th International Conference on Metallurgy and Materials, Hotel Voronez I, Brno, Czech Republic, EU, May 24th - 26th 2017
Proceedings:
Proceedings 26th International Conference on Metallurgy and Materials
Pages:
2104-2108
ISBN:
978-80-87294-79-6
ISSN:
2694-9296
Published:
9th January 2018
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
34 views / 7 downloads
Abstract

Coke is one of the basic energy sources in the blast furnace process. Its quality essentially then determines the course of the blast furnace process. It is used both in the blast furnace and in the agglomeration processes. Coke also significantly affects the price of the produced raw metal. A number of different categorical criteria can be used for its evaluation. It may be the chemical, physical, technical, mechanical and logistic properties, but also cost. Apart from the chemical composition, typical properties of coke include also strength, grain composition, moisture content, heating value and a number of other parameters. If the evaluation of coke were based only on isolated criteria, finding the best possible choice would be complicated. One option for evaluating multidimensional problems are mathematical multi-criteria decision tools. These methods allow assessment of the difficult and complex issues through dozens of completely different criteria. As part of the research, these methods have been used to experimentally assess the quality of the supplied coke. The article deals with the analysis applied to the assessment process of the quality of blast furnace coke and use of this methodology in metallurgical enterprises.

Keywords: iron, process, Sulphur, costs, production
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