Statistical modeling of charcoal consumption of blast furnaces based on historical data
Source abstract
Abstract
This paper describes the development of statistical models to predict charcoal consumption in blast furnaces based on Response Surface Models (RSM) and Linear Regression Models (LRM). The statistical approach used provides a high level of confidence and allows the company to act preemptively fostering innovative business and in the action plan to reduce hot metal production cost, to improve raw materials processing and other actions in order to provide the blast furnaces with raw materials at minimal cost. It is a special particularity and represents a great step in V & M do Brasil blast furnaces’ operation which no longer uses standard ferrous load and started to operate with greater flexibility and variability concerning the types of ferrous load applied to achieve better economic results.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Iron and Steelmaking Processes · Metallurgical Processes and Thermodynamics · Mineral Processing and Grinding
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (20)
Show source-provided references
1. A chaos-based iterated multistep predictor for blast furnace iron making process10.1002/aic.11724 ↗
2. Mathematical Modeling of Closed-loop Intelligent Control for B.F. Iron-making Process. icicta
3. Dynamics models of blast furnace smelting for trainers and researchers10.1007/s11015-008-9022-2 ↗
4. Multiple correlation of blast furnace variables
5. Fault diagnosis of the blast furnace based on the Bayesian network model
6. Controle estatístico de processo aplicado a produção de gusa em usinas não integradas a carvão vegetal
7. A refined prediction model of silicon content based on the Kalman Filter
8. Thomson · 2005 · 180
9. Subspace method of identification and control of blast furnace ironmaking process
10. Modeling for control of blast furnace
11. VAI blast furnace automation – a powerful solution for highest production economy
12. Castro · 2002 · 155
13. Utilização de redes neurais artificiais e modelo CFD como estratégia para tomada de decisões no processo do alto-forno
14. Modelagem do nível térmico de um alto-forno para aumento da eficiência operacional utilizando redes neurais artificiais
15. Aplicações da mecânica dos fluidos computacional na indústria siderúrgica
16. An application of prediction model in blast furnace hot metal silicon content based on neural network
17. Improvement in performance of the blast furnace at Bhilai through statistical analysis and improvement in burden preparation10.2355/isijinternational.31.669 ↗
18. Exigências metalúrgicas para o carvão vegetal em mini altos-fornos e fornos elétricos de redução
19. Cruz · 2007 · 108
20. Montgomery · 2004 · 335