Title :
An Empirical Model of the Decarburization Process in Stainless Steel Production
Author :
Spínola, Carlos ; Galvez-Fernandez, C.J. ; Munoz-Perez, J. ; Jerrer, Javier ; Bonelo, José M. ; Vizoso, Julio
Abstract :
The argon-oxygen decarburization (AOD) is the refining process of stainless steel to get its final chemical composition through several stages where tons of materials are added and oxygen and inert gas are blown. We present in this paper the design of an empirical model of this process to predict critical values of the decarburization process in order to automate it and enhance the production performance of the AOD. We show that it is possible to build an empirical model, simpler than analytical parameterized models, based on Multilinear Regression or Neural Network Perceptron to predict the amount of oxygen to be blown and the temperature to be reached.
Keywords :
chemical analysis; refining; stainless steel; steel manufacture; AOD; FeCrCJk; argon-oxygen decarburization; chemical composition; decarburization process; multilinear regression; neural network perceptron; refining process; stainless steel production; Analytical models; Building materials; Chemical processes; Composite materials; Neural networks; Predictive models; Production; Refining; Steel; Temperature;
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
DOI :
10.1109/ICIT.2006.372501
