arXiv:2412.00209cs.AI2024-12综述被引 63

全面梳理工业数字孪生技术应用与挑战,揭示其跨领域融合价值

Digital Twin in Industries: A Comprehensive Survey

  • 系统梳理数字孪生核心技术与工业服务集成路径
  • 覆盖制造、医疗、能源等八大领域,分析真实场景落地能力
  • 聚焦数据通信、隐私安全等关键问题,提出未来研究方向

工业网络正因新兴技术融合而快速转型,显著提升运营效率并重塑产业格局。在此背景下,数字孪生(Digital Twin, DT)作为连接物理与数字世界的创新技术,日益成为核心驱动力。本文全面综述了DT在工业领域的服务与应用,从基础概念与构成出发,探讨关键使能技术。不同于已有研究,本文深入分析了DT在数据共享、边缘计算、感知通信一体化、内容缓存、资源调度、无线网络及元宇宙等多类工业服务中的能力。重点阐述了其在制造、医疗、交通、能源、农业、航天、油气及机器人等领域的技术角色。通过分析物理与虚拟平台间的实时数据交互机制,构建工业数字孪生网络架构。进一步系统探讨了基于数字孪生的工业系统中广泛存在的隐私与安全问题。文章提供分类表格与核心研究发现,强调数字孪生在工业变革中的关键意义,并指明未来研究方向,以推动该前沿领域的持续发展。

原文摘要 · Abstract (English)

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. In this article, we present a comprehensive survey of the emerging DT-enabled services and applications across industries, beginning with an overview of DT fundamentals and its components to a discussion of key enabling technologies for DT. Different from literature works, we investigate and analyze the capabilities of DT across a wide range of industrial services, including data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. In particular, we present an in-depth technical discussion of the roles of DT in industrial applications across various domains, including manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Throughout the technical analysis, we delve into real-time data communications between physical and virtual platforms to enable industrial DT networking. Subsequently, we extensively explore and analyze a wide range of major privacy and security issues in DT-based industry. Taxonomy tables and the key research findings from the survey are also given, emphasizing important insights into the significance of DT in industries. Finally, we point out future research directions to spur further research in this promising area.

数字孪生工业互联网跨域融合安全隐私

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