The Digital Twin Consortium (DTC) has recently announced updated definitions for the terms “digital twin” and “digital thread”, aligning these concepts more closely with fundamental digital engineering principles. These revised definitions highlight the vital role of digital twins and threads in advanced digital engineering, reinforcing their significance in building data-driven ecosystems across a range of industries.
“Our updated definitions reflect the evolving landscape of digital engineering. By aligning our terminology with established digital engineering principles, we’re fostering a common understanding that bridges multiple sectors and applications over the digital twin lifecycle,” explained Dan Isaacs, GM and CTO of the DTC. “These revisions underscore DTC’s commitment to creating an aligned and more unified understanding of real-world application digital twins that bridge theoretical concepts with practical applications. DTC members are working together to foster greater understanding, more transparent communication for more effective collaboration, and accelerated innovation and adoption throughout the digital twin ecosystem.”
“The revised digital twin definition emphasises synchronisation and data, with a model-based approach tied to engineering technology. Grounded in physics, it supports the full life cycle from simulation to decommissioning digital twins. By refining this definition, we enable more accurate, real-time representations, leading to better decisions, improved efficiencies, and deeper insights across industries,” said Dr. David McKee, Co-chair of the DTC Capabilities and Technology Working Group and Lead Author of the DTC Definition Team. “Intrinsically linked to the digital twin, the refined digital thread definition highlights critical elements, including seamless, secure data flow across the product lifecycle and all organisations, silos, and stakeholders. Focusing on trust, security, and reliability provides digital twins’ assured foundation and lifeblood for confident decision-making and continuous improvement.”
The updated definitions are now more closely aligned with the language of the National Academies of Sciences, Engineering, and Medicine. This includes an emphasis on the mirroring of system structures, contexts, and behaviours, as well as dynamic updates, bidirectional interaction, predictive capabilities, and value-driven decision-making, as outlined in the 2024 Foundational Research Gaps and Future Directions for Digital Twins report.
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