刘青, 邵鑫, 杨建平, 张江山. 炼钢厂多尺度建模与协同制造[J]. 工程科学学报, 2021, 43(12): 1698-1712. DOI: 10.13374/j.issn2095-9389.2021.09.27.010
引用本文: 刘青, 邵鑫, 杨建平, 张江山. 炼钢厂多尺度建模与协同制造[J]. 工程科学学报, 2021, 43(12): 1698-1712. DOI: 10.13374/j.issn2095-9389.2021.09.27.010
LIU Qing, SHAO Xin, YANG Jian-ping, ZHANG Jiang-shan. Multiscale modeling and collaborative manufacturing for steelmaking plants[J]. Chinese Journal of Engineering, 2021, 43(12): 1698-1712. DOI: 10.13374/j.issn2095-9389.2021.09.27.010
Citation: LIU Qing, SHAO Xin, YANG Jian-ping, ZHANG Jiang-shan. Multiscale modeling and collaborative manufacturing for steelmaking plants[J]. Chinese Journal of Engineering, 2021, 43(12): 1698-1712. DOI: 10.13374/j.issn2095-9389.2021.09.27.010

炼钢厂多尺度建模与协同制造

Multiscale modeling and collaborative manufacturing for steelmaking plants

  • 摘要: 在阐述炼钢厂多尺度建模与协同制造技术架构的基础上,分别从单体工序尺度、车间区段尺度与炼钢厂运行尺度开展了炼钢厂协同制造的研究。从工序/装置过程控制系统(PCS)到炼钢厂制造执行系统(MES)进行了较为系统的建模研发,构建了包括转炉工序、精炼工序与连铸工序在内的工序工艺控制模型以及以生产计划与调度模型为核心的物质流运行优化模型,并通过工序工艺控制和生产计划与调度的动态协同,实现了炼钢厂多工序/装置的高效运行。研发了炼钢−连铸过程工序工艺控制模型、生产计划与调度模型同MES之间的数据接口,实现了MES与生产工艺控制、流程运行控制、生产计划与调度系统的有机融合,形成了以机理模型与数据模型协同驱动的工艺精准控制、多工序协同运行、基于“规则+算法”的生产计划与调度为支撑的炼钢−连铸过程集成制造技术,通过多层级的纵向协同与多工序的横向协同,实现了炼钢厂的协同运行与控制。研究成果是炼钢−连铸过程智能制造的有益探索与实践,对流程工业智能制造企业具有很强的参考价值,对冶金工业绿色化、智能化发展具有示范与借鉴作用。应用后,明显提升了炼钢厂的协同制造水平,取得了显著的经济与社会效益。

     

    Abstract: With the recent, rapid developments of metallurgical theory and intelligent steelmaking technology, the intelligent upgrading of iron and steel enterprises has attracted increased attention and become a topic of discussion in the steel industry. Collaborative manufacturing is an important feature of intelligent manufacturing in steel enterprises, and it plays an important role in improving the production efficiency and reducing the carbon emissions of iron and steel enterprises. This study elaborated the structure and the contents of multiscale modeling and the collaborative manufacturing of steelmaking plants in detail. The collaborative control of steelmaking plants was studied from the scales of individual processes, workshop sections, and the operation of steelmaking plants. Systematic modeling studies had been conducted from the process control system of processes/devices to the manufacturing execution system (MES). The process control models, including the converter steelmaking process, secondary metallurgy process, and continuous casting process, and mass flow operation optimization models with the production planning and scheduling model as the core were established. In addition, the high-efficiency operation of multi processes/devices was realized through the dynamic coordination of process control and production planning and scheduling in the steelmaking plants. The data interface between process control models, production planning and scheduling models, and MES had been developed to realize the comprehensive integration of MES, production process control, process operation control, production planning, and scheduling system. It had formed the steelmaking-continuous casting process integrated manufacturing technology supported by the precise process control co-driven by mechanism and data models, collaborative process operation, and production planning and scheduling based on “rules + algorithms.” Through multilevel vertical coordination and multiprocess horizontal coordination, the coordinated operation and the control of steelmaking plants were realized. The study results demonstrated a beneficial exploration and the practice of intelligent manufacturing in the steelmaking-continuous casting process, which had strong reference value for intelligent manufacturing enterprises in the process industry, and had a demonstration effect for the green and the intelligent development of the metallurgical industry. After the application, the collaborative manufacturing level of the steelmaking plant had been considerably improved, and significant economic and social benefits had been achieved.

     

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