Speaker
Description
In the last decades, steelmaking processes have been a subject to substantial modernization in terms of digitalization and informatization of various plants. Whether in the past operational measurements acquired by SCADAs have been used solely for process monitoring and fault detection, a closer inspection of the gathered data reveals numerous possibilities also for process enhancement and optimization. As such, modern methods of modelling, simulation and data mining can be applied using vast amounts of historical data, aiming to improve different processes in different steelmaking areas. The following paper presents the means and the methods of digital transformation of the electric-arc-furnace (EAF) process in SIJ Acroni steelworks. The work as presented in this paper is performed in the scope of the ongoing EU Horizon 2020 project, SPIRE initiative, INEVITABLE (“Optimization and performance improving in metal industry by digital technologies”, Grant No. 869815). In this manner, different aspects and approaches of digitalization, and more important, proper software tools, to support and enhance the EAF process, are presented. First, the overall concept of digitalization, including data acquisition, protocols and data transfers, is presented, representing the fundamentals for higher software levels. Second, the developed methods, which aim to increase the efficiency of the EAF, are discussed in greater detail, explaining the concepts of theoretical modelling and parallel simulation, fuzzy-model based solutions and data-driven process optimization, in terms of energy and resource use. Third, the planned implementation of the developed methodology is presented, including the envisioned application of edge computing and cloud-based user interfaces. Finally, some of the proposed goals and expectations from the developed solutions are explained and discussed.