abstract
- The basic oxygen furnace (BOF) is responsible for over 60% of the steel production worldwide. Despite being an old and intensively studied process, the complex dynamics of the phenomena taking place in the BOF still challenge researchers and fuel debates. Moreover, the severe operational conditions often prevent direct/continuous measurements of the states, making the process operation largely dependent on past experience and operators' knowledge. In this work, a dynamic model and optimization framework that can aid operators with the decision-making process are developed. Through several case studies, it is shown that the developed framework can potentially be used to reduce operational costs and increase productivity.