This technology relates to an artificial neural network-based annealing furnace prediction method and apparatus for maintaining the quality of steel products during continuous operation. In particular, it is a technology designed to enhance performance, durability, stability, and applicability based on the core materials, structures, processes, or apparatus configurations related to the artificial neural network-based annealing furnace prediction control method and apparatus.
By providing a more accurate and automated control system, this technology resolves the problem of inaccurate temperature control in an annealing furnace, which leads to a decrease in steel quality. Accordingly, this technology proposes a technical concept that utilizes an artificial neural network-based annealing furnace prediction method, which includes the step of receiving the current temperature of the annealing furnace, the characteristics of the steel fed into the annealing furnace, and time-series input data, as a core means, and implements the use of an artificial neural network to predict and control the temperature of the annealing furnace based on time-series input data.
Accordingly, this invention is expected to improve the accuracy and automation of temperature control in an annealing furnace, thereby inducing the production of higher-quality steel, and can simultaneously enhance reproducibility, scalability, and process suitability in actual operating environments. Furthermore, it can be utilized as a high-performance material, component, battery, sensor, device, or manufacturing process in related industries, making it advantageous in terms of subsequent commercialization and demonstration development.
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