Improving the Intensity of the Steelmaking Technological Process Based on Fuzzy Logic

This article analyzes the application of a fuzzy logic system for controlling complex and uncertain technological processes occurring in a 30-ton Electric Arc Furnace (EAF-30). Research findings show that 80% of the melting process (42 minutes) is carried out using an electric arc. In traditional control systems, rapid fluctuations in arc current exceeding or falling below 17 kA have been identified as a cause of process interruptions. Therefore, this study proposes the fuzzification of arc current, voltage, and arc length using Gaussian membership functions. Based on critical thresholds—arc current in the range of 17–38 kA and voltage from -6% to +8%—linguistic variables were developed. Using the Mamdani algorithm, optimal electrode control during the 17–20-minute melting phase ensures improved energy efficiency, reduced electrode consumption, and increased product output. The research results demonstrate that integrating Fuzzy control into traditional systems is an effective approach for intensifying the steelmaking technological process.