A review of data-driven digital twin resource management for smart steel industry
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全球工业4.0革命不断深化推动了智慧钢铁等计算密集型工业应用场景的发展.钢铁生产具备工艺繁多、工序复杂、高温高压设备集中等特征,这需要对生产状态进行实时监测与分析以优化生产流程.由于各工序均为"黑箱",导致实时状态难以精准获取等难题.数字孪生(digital twin,DT)技术通过创建物理世界的虚拟映射,已广泛应用于辅助钢铁生产过程实现实时模拟、分析和透明化,进而促进生产效率和质量的提升.首先提出了基于DT的云边端工业网络的多层协作调度框架,为实现资源的高效管理和网络安全,从网络层深入分析DT赋能下的工业互联网(industrial Internet of things,IIoT)新型资源调度与网络安全关键技术难点并探讨现有技术方案;然后聚焦物理层与数据链路层讨论孪生数据使能的跨层资源调度策略研究现状.最后指出现有工作不足并展望DT赋能的智慧钢铁的资源管理发展趋势,为钢铁行业的数字化转型提供参考.
The continuous deepen of the global Industry 4.0 revolution has driven the development of computationally intensive industrial applications such as smart steel.Steel production,characterized by diverse processes,complex procedures,and concentrated high-temperature and high-pressure equipment,necessitates real-time monitoring and analysis of production status to optimize production processes.Due to the opaque nature of each process,with real-time status being difficult to accurately obtain,digital twin(DT)technology offers a solution by facilitating real-time simulation and transpar-ency in steel production,thus improving efficiency and quality.A multi-layer collaborative scheduling framework for industrial networks based on DT is presented,aiming to enhance resource management and network security.Challenges and explores solutions for novel resource scheduling and network se-curity under DT-enabled industrial Internet of things(IIoT)is analyzed.Moreover,the exploration of cross-layer resource scheduling strategies attracts extensive focus,facilitated by twin data at both the physical layer and data link layer.Finally,it points out the emerging trends in DT-enabled smart steel resource management,offering valuable insights for the digital transformation of the steel industry.
NETL
NSTL
万方数据
