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.

Authors

Institutions

Publication Details

Journal
Sanoatda raqamli texnologiyalar.
Published
2025-08-16
DOI
https://doi.org/10.70769/3030-3214.srt.3.3.2025.7
Primary Topic
Fuzzy Logic and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

IMPROVING THE INTENSITY OF THE STEELMAKING TECHNOLOGICAL PROCESS BASED ON FUZZY LOGIC

Ikromjon Rakhmonov, Makhzuna Korjobova
Sanoatda raqamli texnologiyalar.
Fuzzy Logic and Control Systems
article

IMPROVING THE INTENSITY OF THE STEELMAKING TECHNOLOGICAL PROCESS BASED ON FUZZY LOGIC

Ikromjon Rakhmonov, Makhzuna Korjobova
article en

Abstract

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.

Sanoatda raqamli texnologiyalar.Vol. 3(3)
Tashkent State Technical University named after Islam Karimov (UZ)
Openalex Percentile: Top 89%
Fuzzy Logic and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

IMPROVING THE INTENSITY OF THE STEELMAKING TECHNOLOGICAL PROCESS BASED ON FUZZY LOGIC — Ikromjon Rakhmonov, Makhzuna Korjobova · Sanoatda raqamli texnologiyalar. (2025) | TGRS Research Map | TGRS