Use of Artificial Neural Networks in Steelmaking Oxygen Converters

Zusatztext

Decarburization is the most important reaction in the primary refining process via Oxygen Converter, since it can govern the productivity of an entire melt shop. Thus, the control of the main variables of this process such as the end time of oxygen blowing and the final carbon content of the bath is of utmost importance. For that, this book deals with the development of a mathematical model, using tools of artificial intelligence such as artificial neural nets (RNAs), to predict these variables from the analysis of the oxygen converter outlet gases. The model calculates the end blow time and the final carbon content in the liquid steel and it showed good correlation with real data from a steel mill.

Autorenportrait

Professor at the Federal Institute of Minas Gerais, he is the leading researcher of CNPq's Research Group called "Núcleo de Pesquisa em Processos e Produtos Siderúrgicos". He has experience in the steelmaking area as a research engineer for Gerdau S.A. in the development of new steel.

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