数字孪生中的知识图谱：关于工业自动化中语义技术与仿真结合的系统性文献综述
Knowledge Graphs in the Digital Twin: A Systematic Literature Review About the Combination of Semantic Technologies and Simulation in Industrial Automation
AI总结：
本文通过系统性文献综述，探讨了在工业自动化数字孪生框架中利用知识图谱实现仿真模型自动适应、配置与生成的技术方案，以解决可扩展性和维护挑战。
摘要：
随着数字孪生的出现，工业部门持续进行的数字化已到达一个关键节点，它提供了物理资产和过程的数字化表示。这些数字化表示的一个关键方面是仿真模型，它能够更深入地洞察资产的当前状态及其特征。本文断言，这一数字化旅程的下一个演进步骤涉及在数字孪生框架内整合不同仿真模型之间的智能链接。至关重要的是，为了使数字孪生成为一种可扩展且具有成本效益的解决方案，迫切需要实现仿真模型的自动适应、（重新）配置和生成。认识到实现此类自动化所固有的挑战，本文分析了知识图谱作为一种潜在非常合适的技术解决方案的利用。知识图谱作为互连和相关的数据库，提供了一种无缝集成不同数据源的手段，促进了数字孪生中数据和（仿真）模型的高效集成与自动适应。我们进行了一项全面的文献综述，以分析数字孪生背景下知识图谱的现状，重点关注仿真模型。通过解决与可扩展性和维护相关的挑战，本研究有助于工业部门有效适应数字孪生，为在不断演进的技术环境中提升效率、适应性和韧性铺平道路。
英文摘要：
The ongoing digitization of the industrial sector has reached a pivotal juncture with the emergence of Digital Twins, offering a digital representation of physical assets and processes. One key aspect of those digital representations are simulation models, enabling a deeper insight in the assets current state and its characteristics. This paper asserts that the next evolutionary step in this digitization journey involves the integration of intelligent linkages between diverse simulation models within the Digital Twin framework. Crucially, for the Digital Twin to be a scalable and cost-effective solution, there is a pressing need for automated adaption, (re-)configuration, and generation of simulation models. Recognizing the inherent challenges in achieving such automation, this paper analyses the utilization of knowledge graphs as a potentially very suitable technological solution. Knowledge graphs, acting as interconnected and interrelated databases, provide a means of seamlessly integrating different data sources, facilitating the efficient integration and automated adaption of data and (simulation) models in the Digital Twin. We conducted a comprehensive literature review to analyze the current landscape of knowledge graphs in the context of Digital Twins with focus on simulation models. By addressing the challenges associated with scalability and maintenance, this research contributes to the effective adaption of Digital Twins in the industrial sector, paving the way for enhanced efficiency, adaptability, and resilience in the face of evolving technological landscapes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
