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Dynamic programming-based computation of an optimal tap working pattern in nonferrous arc furnace

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Abstract

Power is essential in nonferrous arc furnace plants for burning and melting scraps, as well as for the composition of raw materials to produce the furnace product. To ensure high-quality operation, the electric energy is controlled by changing the tap positions. However, there is no standard working pattern to determine the most effective option for changing the tap positions to obtain optimal power and product quantity. This study proposes a method to analyze and determine the working patterns in nonferrous arc furnace plants by adopting dynamic programming. To find the best objective value candidates, statistical methods were utilized to obtain the optimal values of the total elemental power and total product quantity. Moreover, if the maximum product quantity minimum electric consumption are known, the least power per product quantity (PPQ) can be easily obtained. Thus, it is reasonable to analyze the sequences of tap positions and then obtain the best PPQ using an approach of solving a recurrence problem with the widely used dynamic programming approach. We demonstrated that the proposed method suggested the working pattern of tap positions, thereby providing relatively good PPQs in comparison with the conventional method.

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Authors and Affiliations

  1. Department of Computer Science, Chungbuk National University, Cheongju, 28644, Korea

    Sokchomrern Ean, Manas Bazarbaev, Keon Myung Lee, Aziz Nasridinov & Kwan-Hee Yoo

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  1. Sokchomrern Ean
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  2. Manas Bazarbaev
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  3. Keon Myung Lee
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  4. Aziz Nasridinov
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  5. Kwan-Hee Yoo
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Correspondence to Kwan-Hee Yoo.

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Ean, S., Bazarbaev, M., Lee, K.M. et al. Dynamic programming-based computation of an optimal tap working pattern in nonferrous arc furnace. J Supercomput 78, 640–666 (2022). https://doi.org/10.1007/s11227-021-03880-8

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