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基于钢包运行稳定性的炼钢厂生产计划优化
引用本文:冯凯,贺东风,徐安军,汪红兵. 基于钢包运行稳定性的炼钢厂生产计划优化[J]. 东北大学学报(自然科学版), 2015, 36(11): 1619-1623. DOI: 10.12068/j.issn.1005-3026.2015.11.022
作者姓名:冯凯  贺东风  徐安军  汪红兵
作者单位:(1. 北京科技大学 冶金与生态工程学院, 北京100083; 2. 北京科技大学 计算机与通信工程学院, 北京100083)
基金项目:国家重点基础研究发展计划项目(2012CB720405); 中央高校基本科研业务费专项资金资助项目(FRF-TP-14-047A2).
摘    要:针对炼钢厂在不满负荷生产的情况下,缺少相应指导原则编排生产计划的问题,提出一种基于钢包运行稳定性的生产计划优化方法.首先,通过对炼钢厂钢包周转过程的分析,提出在线运行钢包个数的计算方法.然后,分别针对单台铸机和两台铸机顺序开浇的两种情况,分析生产计划对钢包运行状态的影响,建立计算模型.以某炼钢厂生产计划为例进行解析,并以钢包运行稳定性为评价参数,利用遗传算法对生产计划进行优化.结果表明,优化的生产计划可以减少钢包使用个数及其温度波动,减少烘烤煤气消耗量和降低转炉出钢温度,提高钢水温度的控制水平.

关 键 词:生产计划  优化  钢包  遗传算法  能耗  

Optimization of Production Schedule Based on Ladle Running Stability in Steel Plant
FENG Kai,HE Dong-feng,XU An-jun,WANG Hong-bing. Optimization of Production Schedule Based on Ladle Running Stability in Steel Plant[J]. Journal of Northeastern University(Natural Science), 2015, 36(11): 1619-1623. DOI: 10.12068/j.issn.1005-3026.2015.11.022
Authors:FENG Kai  HE Dong-feng  XU An-jun  WANG Hong-bing
Affiliation:1. School of Metallurgy and Ecology Engineering, University of Science and Technology Beijing, Beijing 100083, China; 2. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Abstract:For the problem of the lack of guiding principle of production schedule in the case of non-full production in steelmaking plant, the optimization method of production schedule based on ladle running stability was proposed. First, the computational method of the number of online operation ladle was proposed by analyzing ladle turnaround process. Second, the impact of production schedule on ladle running was analyzed for the production schedule of single casting machine and two casting machine, and the computational model was proposed. Finally, the method was used to optimize actual production schedule of a steelmaking plant. The results showed that using genetic algorithm based on ladle running stability, the fluctuation of the number of ladle is reduced, the fluctuation of ladle thermal state is reduced, baking gas is saved, the temperature of BOF endpoint is reduced and the level of control the temperature of molten steel is improved.
Keywords:production schedule  optimization  ladle  genetic algorithm  energy consumption  
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