深入认识钢铁制造流程的动态运行特征是实现流程动态-有序、协同-连续运行状态管控的基础。基于对钢铁生产流程特征的分析,阐述了“流、流程网络与运行程序”作为钢铁制造流程动态运行3大要素的特征及其数学描述,明确了运行程序是进行物质流、能量流在以流程网络为基础的网络空间中运行优化的调控手段,以及构建铁素物质流及能量流在流程网络上的动态运行优化模型是实现钢铁制造流程高效优质低耗低成本运行的有效途径。对于钢铁制造企业,提出了以生产计划调度优化模型为核心的运行程序优化技术,通过优化模型形成的生产计划调度指令可引导制造流程运行状态的整体优化,实现生产资源的合理优化配置和能源利用效率提升。
Abstract
In-depth understanding of the dynamic operating characteristics of the steel manufacturing process is an important basis for realizing dynamic-orderly, collaborative-continuous operating status. Based on the characteristics analysis of steel production process, the characteristics and mathematical descriptions of "flow, flow network, operating program", which are the three major elements of the dynamic operation of the steel manufacturing process, are elaborated. It is clarified that the operating program is the control measure for the operation optimization of material flow and energy flow in the network space based on the flow network. The construction of the dynamic operation optimization model of the ferrite material flow and energy flow on the flow network is an effective way to realize the high-efficiency, high-quality, low-consumption and low-cost operation of the steel manufacturing process. For steel manufacturing enterprises, an operating program optimization technology centered on the production planning and scheduling optimization model is proposed. The production planning and scheduling instructions formed by the optimization model can guide the overall optimization of the operating state of manufacturing process, and realize the reasonable optimization allocation of production resources and the improvement of energy utilization efficiency.
关键词
流 /
流程网络 /
运行程序 /
生产计划调度 /
实践
{{custom_keyword}} /
Key words
flow /
flow network /
operating program /
production planning and scheduling /
practice
{{custom_keyword}} /
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 殷瑞钰. 冶金流程工程学[M]. 北京:冶金工业出版社, 2009.(YIN Rui-yu. Metallurgical Process Engineering[M]. Beijing: Metallurgical Industry Press,2009.)
[2] YIN Rui-yu. Metallurgical Process Engineering[M]. Beijing:Metallurgical Industry Press,2011.
[3] 殷瑞钰. 关于智能化钢厂的讨论——从物理系统一侧出发讨论钢厂智能化[J]. 钢铁, 2017,51(6):1.(YIN Rui-yu. A discussion on:"Smart" steel plant—view from physical system side[J]. Iron and Steel, 2017,51(6):1.)
[4] 殷瑞钰. 关于钢铁制造流程的研究[J]. 金属学报, 2007(11):3.(YIN Rui-yu. Some science problem about steel manufacturing process[J]. Acta Metallurgica Sinica,2007(11):3.)
[5] 张福明.智能化钢铁制造流程信息物理系统的设计研究[J].钢铁,2021,56(6):1.(ZHANG Fu-ming. Research and design on cyber physics system of intelligent iron and steel manufacturing process[J]. Iron and Steel, 2021,56(6):1.)
[6] 颉建新,张福明. 钢铁制造流程智能制造与智能设计[J]. 中国冶金, 2019, 29(2): 1. (XIE Jian-xin,ZHANG Fu-ming. Intelligent manufacturing and intelligent design of iron and steel manufacturing process[J]. China Metallurgy, 2019, 29(2): 1.)
[7] 殷瑞钰. “流”、流程网络与耗散结构——关于流程制造型制造流程物理系统的认识[J].中国科学:技术科学,2018(2):136.(YIN Rui-yu. "Flow", flow network and dissipative structure—Understanding of the physical system of manufacturing process of process manufacturing type[J].Scientia Sinica Technologica,2018(2):136.)
[8] DOI:10.13228/j.boyuan.issn0449-749x.20210084.张福明,颉建新. 冶金流程工程学的典型应用[J].钢铁,2021,56(8):10.(ZHANG Fu-ming,XIE Jian-xin. Typical application of metallurgical process engineering[J]. Iron and Steel, 2021,56(8):10.)
[9] 殷瑞钰. 论钢厂制造过程中能量流行为和能量流网络的构建[J]. 钢铁, 2010,45(4):5.(YIN Rui-yu. Comment on behavior of energy flow and construction of energy flow network for steel manufacturing process [J]. Iron and Steel, 2010,45(4):5.)
[10] 燕飞, 范军, 吴礼云,等. 基于物质流、能量流与信息流的钢铁厂智能调控系统架构研究[J]. 冶金自动化, 2018, 42(3):24.(YAN Fei, FAN Jun, WU Li-yun, et al. Research on intelligent control system framework of iron and steel plant based on material flow,energy flow and information flow[J]. Metallurgical Industry Automation,2018,42(3):24.)
[11] 郑忠, 黄世鹏, 李曼琛,等. 钢铁制造流程的物质流和能量流协同优化[J]. 钢铁研究学报, 2016, 28(4):1.(ZHENG Zhong, HUANG Shi-peng, LI Man-chen.et al. Synergetic optimization between material flow and energy flow in steel manufacturing process[J]. Journal of Iron and Steel Research, 2016, 28(4):1.)
[12] 孙彦广. 钢铁工业智能制造的集成优化[J]. 科技导报, 2018, 36(21):30.(SUN Yan-guang. On integrated optimization for steel intelligent manufacturing[J]. Science and Technology Review, 2018, 36(21):30.)
[13] 郑忠, 王永周, 卢义,等. 中厚板组板及板坯设计的智能优化模型和系统[J]. 钢铁, 2020, 55(4):53.(ZHENG Zhong, WANG Yong-zhou, LU Yi, et al. Intelligent optimization model and system of plate and slab design of medium steel plate[J]. Iron and Steel, 2020, 55(4):53.)
[14] 郑忠,王永周,卢义,等. 考虑铸轧协调的炼钢-连铸-热轧一体化生产计划[J]. 钢铁, 2020, 55(12):107.(ZHENG Zhong, WANG Yong-zhou, LU Yi, et al. Integrated production planning of steelmaking-continuous casting-hot rolling considering coordination between casting and rolling[J]. Iron and Steel, 2020, 55(12):107.)
[15] 徐兆俊,郑忠,高小强.炼钢连铸生产调度的优先级策略混合遗传算法[J]. 控制与决策, 2016(8):1394.(XU Zhao-jun,ZHENG Zhong,GAO Xiao-qiang. HGA combined with priority strategy for production planning of steelmaking-continuous casting [J]. Control and Decision,2016(8):1394.)
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
基金
国家自然科学基金重点资助项目(51734004);国家重点研发计划资助项目(2017YFB0304000)
{{custom_fund}}