Paper
4 November 2024 Research on primary aluminum production scheduling optimization based on expert system and long-short-term memory network (LSTM)
Fatao Qin, Chang Wang, Guanglei Zhang, Chenggang Yu, Guangbing Pu, Xiaoyang Li, Xueyan Wei
Author Affiliations +
Proceedings Volume 13420, Third International Conference on New Materials, Machinery, and Vehicle Engineering (NMMVE 2024); 134200B (2024) https://doi.org/10.1117/12.3054947
Event: International Conference on New Materials, Machinery, and Vehicle Engineering 2024, 2024, Dalian, China
Abstract
This article studies the influence of the material and thermal balance of the electrolytic cells in the aluminum production. Specifically, these two metrics reflect the current efficiency, material utilization rate and the lifespan of the electrolytic cells. Therefore, reasonable planning of the amount of siphon aluminum(yield) and production time are two key factors in the aluminum electrolysis process. However, due to the occurrence of numerous emergencies in the actual production process, manual scheduling aluminum production is still a major challenge, which motivate us to develop an LSTM of the rule-based expert system aluminum production decision-making model. First, the input dataset are processed and selected according to the expert system. Then, a deep LSTM model is built. Finally, the output results are planned and maintained based on the expert system. The performance in the experiments also proves that the method is feasible in terms of both accuracy and robustness aspects.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Fatao Qin, Chang Wang, Guanglei Zhang, Chenggang Yu, Guangbing Pu, Xiaoyang Li, and Xueyan Wei "Research on primary aluminum production scheduling optimization based on expert system and long-short-term memory network (LSTM)", Proc. SPIE 13420, Third International Conference on New Materials, Machinery, and Vehicle Engineering (NMMVE 2024), 134200B (4 November 2024); https://doi.org/10.1117/12.3054947
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KEYWORDS
Aluminum

Electrolytes

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