Development and Implementation of Decision Support Systems for Blast Smelting Control in the Conditions of PrJSC “Kamet-Steel”

Abstract

This article presents a description of three decision support systems (DSS) in the mode of an adviser to the technological personnel of blast furnaces (BF), which were implemented by the Iron and Steel Institute of Z.I. Nekrasov (Dnipro, Ukraine) or underwent pilot testing as part of the automated control system of the BF shop of PrJSC “Kamet-steel” (Kamianske, Ukraine). The first DSS for managing the thermal state was implemented in 2021; it includes the entire list of information necessary for personnel in a convenient and compact form, generates recommendations in case of technology deviations, and, in the case of incorrect actions by the personnel, signals the need for correct actions. The main recommendations from the DSS are to correct the raceway adiabatic flame temperature, coke consumption when its characteristics are specified in (indicators of strength and abrasion, fractional composition, humidity, ash and sulfur), and ore load change. Using the system allows both reducing the specific coke consumption and preventing unplanned downtime. The second DSS for controlling the distribution of fuel additives over air tuyeres is based on information on thermal loads determined on water-cooled elements of tuyere tools. The main recommendations from the DSS are to adjust the amount of injected pulverized coal fuel on individual tuyeres in order to ensure a uniform distribution of the raceway adiabatic flame temperature around the circumference of the BF and, as a result, the energy efficiency of BF smelting. The third DSS for adjusting the parameters of the charging mode is based on information from the means of controlling the temperatures of the gas flow above the surface of the charge in the BF. The functioning of this DSS is based on determining the reference curves for the distribution of the gas flow along the BF radii, corresponding to the minimum consumption of coke and maximum productivity, and on the search for solutions by direct and iterative optimization methods, which allow one, by adjusting the charging parameters, to ensure a rational distribution of charge materials and gas flow in the BF.