Steel Scrap Yield Prediction in Basic Oxygen Steelmaking Based on Random Forest and Neural Networks

steel research international, vol. 96

Abstract

Steel scrap is a primary raw material in basic oxygen steelmaking. However, its yield is influenced by numerous factors, making accurate prediction challenging. This study explores and predicts the steel scrap yield in the basic oxygen steelmaking process using machine learning techniques. First, the interquartile range method is applied to clean the collected steelmaking process data. By analyzing the blow loss of molten iron and the amount of steel obtained from the scrap, a deviation coefficient of scrap yield is defined and calculated. Next, a correlation analysis and a feature importance analysis using the random forest algorithm identify the factors influencing the deviation coefficient of scrap yield. Finally, a multilayer neural network regression model is constructed to predict the deviation coefficient of scrap yield. The model achieves a mean squared error of 0.00051 on the test set, with an accuracy rate of 96.89% for absolute errors within ±0.05. This method not only effectively predicts scrap yield but also provides a reference for calculating steel materials and controlling costs in the steelmaking process.

Authors 3

1. Chaojie Zhang Aachen Institute of Metal Forming

   RWTH Aachen University · Anhui University of Technology

   Affiliation as printed

   Institute of Metal Forming RWTH Aachen University Intzestraße 10 52072 Aachen Germany

   School of Metallurgical Engineering Anhui University of Technology Maanshan Anhui 243002 China

   School of Metallurgical Engineering, Anhui University of Technology, Maanshan, Anhui, 243002 China

2. Liqiang Zhang corresponding

   Anhui University of Technology

   Affiliation as printed

   School of Metallurgical Engineering Anhui University of Technology Maanshan Anhui 243002 China

   School of Metallurgical Engineering, Anhui University of Technology, Maanshan, Anhui, 243002 China

3. Jinjun Cheng

   Anhui University of Technology

   Affiliation as printed

   School of Metallurgical Engineering Anhui University of Technology Maanshan Anhui 243002 China

   School of Metallurgical Engineering, Anhui University of Technology, Maanshan, Anhui, 243002 China