Work

Statistical modeling of charcoal consumption of blast furnaces based on historical data

Year: 2013

Type: article

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: Journal of Materials Research and Technology

DOI: 10.1016/j.jmrt.2013.04.002

Authors: Rosiane Mary Rezende Faleiro, Cláudio Musso Velloso, Luiz Fernando Andrade de Castro, Ronaldo Santos Sampaio

Institutions: Universidade Federal de Minas Gerais, Instituto Australis, Instituto Ivoti

Language: English

Topic: Iron and Steelmaking Processes

Subfield: Metals and Alloys

Field: Materials Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,640