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Dephosphorization Ladle Matching Method with Data Analytics in the steelmaking-continuous Casting Process

Dephosphorization Ladle Matching Method with Data Analytics ...

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第31届中国过程控制会议（CPCC2020）

作者： LIU Wei PANG Xinfu LI Haibo YU Shenping YU Zixiang School of Automation Shenyang Institute of Engineering State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

For the matching of dephosphorization ladle for the heats according to the steelmaking-continuous casting production process, multiple conflicting objectives and conflicting constraints must be met. It is difficult to use the existing optimal scheduling method. Artificially preparing matching plans based on experience resulted in the time spent for the preparation of plans, and the number of ladles used online was high, and the hit rate of start-to-off times was low. The dephosphorization ladle matching model was established in the steelmaking-continuous casting production process. The ladle temperature is the highest, the longest life is the longest, and the remaining online use time is the maximum performance index. The constraint equations are established under the constraints of the process ladle temperature, service life, and maintenance end time. The decision variable is the dephosphorization ladle. Using intelligent methods based on first-order rule learning, rule-based reasoning with minimum generalization and the characteristics of ladle matching process, an intelligent matching method for dephosphorization ladle was proposed. The developed matching method was successfully applied to a steelmaking and continuous casting production line in China. Through the analysis of the experimental results, the highly effective proposed the algorithm is compared with previously used method. It brings significant social and economic benefits to the company.

关键词： steelmaking-continuous Ladle matching First-order rule learning Minimal generalization Heuristic

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