Optimization Analysis and Standardization of Rolling Process with Machine Learning

Seongwoo Cho, Yujin Jung, Yongdeuk Seo, Kyuheon Jung, Sungchul Choi

Abstract: This study proposes a model based on machine learning(ML) for predicting the thickness of a coil in a steel rolling process. To achieve this objective, it is necessary to establish an engineering strategy based on data collected from actual rolling sites and to develop multiple models. Five models are trained on preprocessed process data, and the optimal model is determined through experiments.