Digital Transformation of Pyrometallurgical Technologies. State, Scientific Problems, and Prospects of Development - Spirin, N. A.; Lavrov, V. V.; Rybolovlev, V. Yu; Schnaider, D. A.; Krasnobaev, A. V.; Gurin, I. A. (Steel in translation, 2021)
The article provides an overview and critical analysis of the digitalization of the leading Russian ferrous metallurgy enterprises in accordance with the Industry 4.0 development concept. This concept provides for the creation of digital twins of pyrometallurgical technologies and the widespread use of machine (technical) vision and artificial intelligence. Examples of domestic industrial systems using machine (technical) vision, digital assistants (twins) of metallurgical facilities and their complexes in the production cycle are presented. Technical vision systems used to control the processes in the upper and lower zones of blast furnaces are considered with regard to blast-furnace production. A promising area is the integration of technical vision and decision support systems, including algorithms and software modules for implementing deterministic mathematical models of individual blast furnace smelting phenomena. These algorithms and modules are based on the basic physical concepts of blast-furnace smelting processes. One of the main directions of the digital transformation of pyrometallurgical technologies is the creation of intelligent control systems for the real-time management of industrial processes in individual units and their systems in metallurgy. The formulation and solution of tasks require not only studying the characteristics that describe the effect of changes in smelting conditions on the performance indicators of individual furnaces, but also a detailed analysis for mathematically describing external and internal constraints. The authors present examples of subsystems for controlling heat losses in a blast furnace, predicting the parameters of tuyere zones and controlling the distribution of air-blast parameters around the blast furnace perimeter, an automated system of analyzing and predicting production situations in the blast-furnace plant. These systems are based on modern principles and technologies of developing appropriate mathematical, algorithmic and software support.