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Article

Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces

1
Department of Advanced Computational Methods, Faculty of Science and Technology, Jan Dlugosz University in Czestochowa, 13/15 Armii Krajowej Ave., 42-200 Czestochowa, Poland
2
Faculty of Production Engineering and Materials Technology, Czestochowa University of Technology, 19 Armii Krajowej Ave., 42-201 Czestochowa, Poland
3
Faculty of Mechanical Engineering, Czestochowa University of Technology, 21 Armii Krajowej Ave., 42-201 Czestochowa, Poland
*
Author to whom correspondence should be addressed.
Materials 2024, 17(21), 5355; https://doi.org/10.3390/ma17215355
Submission received: 19 September 2024 / Revised: 23 October 2024 / Accepted: 30 October 2024 / Published: 1 November 2024
(This article belongs to the Section Manufacturing Processes and Systems)

Abstract

Heating steel charges is essential for proper charge formation. At the same time, it is a highly energy-intensive process. Limiting the scale formed is critical for reducing heat consumption in this process. This paper applies fuzzy logic to model heating and scale formation in industrial re-heating furnaces. Scale formation depends on the temperature of the initial charge, heating time, excess air coefficient value, and initial scale thickness. These parameters were determined based on experimental tests, which are also the inputs in the model of the analyzed process. The research was carried out in walking beam furnaces operating in hot rolling mill departments. To minimize the excess energy consumption for heating a steel charge in an industrial furnace before forming, a heating and scale formation (HSF) model was developed using the fuzzy logic-based approach. The developed model allows for the prediction of the outputs, i.e., the charge’s final surface temperature and the scale layer’s final thickness. The comparison between the measured and calculated results shows that the model’s accuracy is acceptable.
Keywords: fuzzy logic; artificial intelligence; simulation; heating; scale; steel charge; loss of steel; energy saving fuzzy logic; artificial intelligence; simulation; heating; scale; steel charge; loss of steel; energy saving

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MDPI and ACS Style

Krzywanski, J.; Boryca, J.; Urbaniak, D.; Otwinowski, H.; Wylecial, T.; Sosnowski, M. Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces. Materials 2024, 17, 5355. https://doi.org/10.3390/ma17215355

AMA Style

Krzywanski J, Boryca J, Urbaniak D, Otwinowski H, Wylecial T, Sosnowski M. Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces. Materials. 2024; 17(21):5355. https://doi.org/10.3390/ma17215355

Chicago/Turabian Style

Krzywanski, Jaroslaw, Jaroslaw Boryca, Dariusz Urbaniak, Henryk Otwinowski, Tomasz Wylecial, and Marcin Sosnowski. 2024. "Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces" Materials 17, no. 21: 5355. https://doi.org/10.3390/ma17215355

APA Style

Krzywanski, J., Boryca, J., Urbaniak, D., Otwinowski, H., Wylecial, T., & Sosnowski, M. (2024). Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces. Materials, 17(21), 5355. https://doi.org/10.3390/ma17215355

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