Optimization of the Continuous Casting Process of Hypoeutectoid Steel Grades Using Multiple Linear Regression and Genetic Programming—An Industrial Study

Miran Brezocnik,Uroš Župerl

doi:10.3390/met11060972

Abstract

Štore Steel Ltd. is one of the major flat spring steel producers in Europe. Until 2016 the company used a three-strand continuous casting machine with 6 m radius, when it was replaced by a completely new two-strand continuous caster with 9 m radius. For the comparison of the tensile strength of 41 hypoeutectoid steel grades, we conducted 1847 tensile strength tests during the first period of testing using the old continuous caster, and 713 tensile strength tests during the second period of testing using the new continuous caster. It was found that for 11 steel grades the tensile strength of the rolled material was statistically significantly lower (t-test method) in the period of using the new continuous caster, whereas all other steel grades remained the same. To improve the new continuous casting process, we decided to study the process in more detail using the Multiple Linear Regression method and the Genetic Programming approach based on 713 items of empirical data obtained on the new continuous casting machine. Based on the obtained models of the new continuous casting process, we determined the most influential parameters on the tensile strength of a product. According to the model’s analysis, the secondary cooling at the new continuous caster was improved with the installation of a self-cleaning filter in 2019. After implementing this modification, we performed an additional 794 tensile tests during the third period of testing. It was found out that, after installation of the self-cleaning filter, in 6 steel grades out of 19, the tensile strength in rolled condition improved statistically significantly, whereas all the other steel grades remained the same.

Highlights

Tensile strength, as a genuine material property, is defined as the maximal stress achieved during stretching of a material before breaking [1,2,3]
On the basis of the Multiple Linear Regression results, it is possible to conclude that the model predicts the tensile strength significantly (p < 0.05, ANOVA, accessed on 28 May 2021), and that 93.5% of total variances can be explained by independent variables’ variances (R-square)
Installed spray nozzles at secondary cooling are prone to clogging, which is influenced by nozzle geometry and water quality

Summary

Introduction

As a genuine material property, is defined as the maximal stress achieved during stretching of a material before breaking [1,2,3]. Few studies are presented where, besides the chemical composition, the influence of solidification on the mechanical properties of steel was elaborated, including continuous casting. Katsuo et al [23] studied crack sensitivities of continuously cast high-alloy and stainless steels related to segregations of sulfur and phosphorus. They conducted hot tensile tests and examined the fracture surface microscopically. The main motive of the research was to acquire good insight into the mechanism of continuous casting of steel, and, to improve the tensile strength of rolled bars after installation of the new two-strand continuous caster. The results of the steelmaking process optimization are outlined, followed by details of the main findings

Materials and Methods

Process Data

Modeling of Tensile Strength

Modeling of Tensile Strength Using Multiple Linear Regression

Modeling of Tensile Strength Using Genetic Programming

Results and Discussion

Conclusions