Determination of the Influence of Steelmaking Parameters on Surface Defects in Quarto Plates

Abstract

This work aimed to establish a relationship between the parameters affecting the steelmaking process and the quality of the quarto plates. We knew that the main causes of product defects in the plates were in the steelmaking process, so we sought to make changes to the process. All units in the steelmaking plant were equipped with sensors to control the working parameters, which were regularly stored in databases. These data are supplemented by the chemical composition of the molten steel at various stages of the process. To organise and analyse the huge amounts of data, data mining tools included in the Orange Software were used. For industrial use, the tree algorithm seems to be the most suitable, but we also used other models based on artificial intelligence. Unexpectedly, we obtained evidence of self-regulation and robustness in the steelmaking process. Another important result was that some additional parameters should be measured and analysed regularly, at least the amount of oligo-elements in the molten steel and the basicity of the final refining slag.

Structural Optimization of Scarfing Machine with Acceleration Profile and Multi-Objective Genetic Algorithm Approach

“…In the steelmaking phase, impurities such as carbon, phosphorus, and sulfur are removed from the metal. However, this process can lead to defects, such as decarburization layers, micro-cracks, rust, and other impurities on the surfaces of slabs and billets [1,2]. Such surface defects can be predicted through thermal transfer analysis [3][4][5].…”