智能数字孪生与复杂系统的开发与管理

Digital Twin Pub Date : 2022-05-25 DOI:10.12688/digitaltwin.17574.1

Michael W. Grieves

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引用次数: 39

摘要

对定义和实施数字双胞胎（DT）的兴趣是当今产品组织的前沿。越来越复杂的系统的进化要求通过数字双胞胎来组织和管理它们的信息。此外，人工智能的发展将导致系统复杂性的增加。当人工智能作为目标寻求和学习的结果修改系统方面时，这些复杂系统将表现出真正的涌现行为。DT需要提高能力，在方法上变得智能。本文讨论了这些智能数字双胞胎（IDT）将如何发展并帮助开发和管理复杂系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Intelligent digital twins and the development and management of complex systems

The interest in defining and implementing Digital Twins (DT) is at the forefront of today’s product organizations. The evolution of increasingly complex systems requires that their information be organized and managed via digital twins. In addition, the development of Artificial Intelligence (AI) will result in an increasing degree of system complexity. These complex systems will exhibit true emergent behavior as AIs modify system aspects as the result of goal seeking and learning. DTs will need to increase in capability, becoming intelligent in their approach. This article presents a discussion on how these Intelligent Digital Twins (IDTs) will evolve and assist in developing and managing complex systems.

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Digital Twin digital twin technologies-

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期刊介绍： Digital Twin is a rapid multidisciplinary open access publishing platform for state-of-the-art, basic, scientific and applied research on digital twin technologies. Digital Twin covers all areas related digital twin technologies, including broad fields such as smart manufacturing, civil and industrial engineering, healthcare, agriculture, and many others. The platform is open to submissions from researchers, practitioners and experts, and all articles will benefit from open peer review.  The aim of Digital Twin is to advance the state-of-the-art in digital twin research and encourage innovation by highlighting efficient, robust and sustainable multidisciplinary applications across a variety of fields. Challenges can be addressed using theoretical, methodological, and technological approaches. The scope of Digital Twin includes, but is not limited to, the following areas:  ● Digital twin concepts, architecture, and frameworks ● Digital twin theory and method ● Digital twin key technologies and tools ● Digital twin applications and case studies ● Digital twin implementation ● Digital twin services ● Digital twin security ● Digital twin standards Digital twin also focuses on applications within and across broad sectors including: ● Smart manufacturing ● Aviation and aerospace ● Smart cities and construction ● Healthcare and medicine ● Robotics ● Shipping, vehicles and railways ● Industrial engineering and engineering management ● Agriculture ● Mining ● Power, energy and environment Digital Twin features a range of article types including research articles, case studies, method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.