The Digital Twin Consortium has expanded its Digital Twin Testbed Programme with the addition of four new testbeds, as the industry pushes beyond conventional digital replicas towards intelligent and generative systems.
The non-profit group said the new projects would provide real-world environments for testing interoperability, validating proof of value, and speeding adoption of digital twin technologies across sectors including manufacturing, energy, healthcare, and smart cities. The announcement was made yesterday in Boston.
Dan Isaacs, GM & CTO of the Digital Twin Consortium, said the programme was designed to move digital twin concepts into operational use. He added that the new testbeds reinforced the organisation’s focus on open standards and cross-industry collaboration, while supporting member-led innovation through shared ecosystems of emerging technologies.
The four testbeds span applications ranging from autonomous manufacturing to climate and public health forecasting.
One project, CAMPUS-SAFE, led by George Mason University, focuses on Covid-19 analysis and mitigation in educational settings. It combines agent-based modelling with campus movement data and environmental monitoring to develop standards for digital health systems and to provide higher education and public health agencies with validated return-on-investment metrics.
A second testbed, MANDATE-R2R Manufacturing, led by the Korea Institute of Machinery and Materials, explores fully autonomous manufacturing. It uses multi-agent digital twins to manage data acquisition, learning, control, and maintenance without human intervention in roll-to-roll electrode production.
The third initiative, Quantum-Powered Optimisation for Digital Twins, led by BQP, integrates quantum-inspired optimisation into high-performance computing environments. The consortium said the approach could explore up to 10,000 design variables while targeting a tenfold reduction in computation time for aerospace and defence applications.
The final testbed, led by Stellar Transformer Technologies, integrates solar-terrestrial lightning and electromagnetic activity data in real time. The project aims to support 2–4-week monsoon forecasting and multi-day lightning hazard warnings, with the goal of reducing fatalities and limiting economic losses linked to extreme weather events.
The Digital Twin Consortium said the testbeds would be developed using its Composability Framework, which includes a business maturity model, platform stack architecture, and a capabilities taxonomy. The framework also incorporates assessments of generative AI, multi-agent systems, and other advanced technologies.
The consortium is part of the EDM Association and works with industry members to promote adoption and interoperability of digital twin technologies across multiple sectors.
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