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Digital Twins for Advanced Manufacturing: The Standardized Approach

Published

Author(s)

Guodong Shao, Deogratias Kibira, Simon P. Frechette

Abstract

Recently, digital twins are becoming more prevalent in a wide range of industries such as manufacturing, construction, smart city, healthcare, business for various purposes including observing, predicting, optimizing, and controlling. However, because digital twins are still in their early adoption stage, in addition to their being interdisciplinary in nature and the complexity involved, there are not so many specific standards that have been developed, and the ecosystem of digital twins has not been well established. Developing and implementing digital twins present significant challenges. Most current digital twin applications take ad hoc approaches with customized solutions, which increase the development time and cost, and make it difficult to integrate with other systems and do not support reuse. Foundational work is needed to support an open marketplace for digital twin developers, users, and technology/service providers. This includes the development of standardized frameworks, reference models, and interfaces to provide a solid foundation for ensuring interoperability, reliability, validity, security, and trust. This chapter focuses on the digital twins for advanced manufacturing, identifies current implementation challenges, reviews relevant standardization efforts, introduces a new ISO digital twin framework standard, presents a few use case scenarios, and discusses some potential research directions and future standardization topics.
Citation
Digital Twins, Simulation, and Metaverse
Publisher Info
Springer Nature, Washington, DC

Keywords

Digital Twin, Standards, Advanced Manufacturing, Robot Workcell.

Citation

Shao, G. , Kibira, D. and Frechette, S. (2024), Digital Twins for Advanced Manufacturing: The Standardized Approach, Digital Twins, Simulation, and Metaverse, Springer Nature, Washington, DC, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957417 (Accessed October 31, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created October 26, 2024, Updated October 27, 2024