Multilayer perceptron to model the decarburization process in stainless steel production
نویسندگان
چکیده
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. The decarburization efficiency and the final temperature in each stage are two important values of this process. We present in this paper an empirical model, based on Multilayer Perceptron, to predict these values in order to automate and enhance the production performance of the AOD. Two architectures are proposed and compared.
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