Digital Twin Consortium Announces Digital Twin Testbed Program
The Digital Twin Consortium (DTC) has announced the first testbeds as part of its Digital Twin Testbed Program. This collaborative member-driven program accelerates development, validation, and implementation, demonstrating digital twin evolution with agentic AI and enabling technologies. By providing unprecedented access to early-stage testbed development, members can model, simulate, integrate, rigorously verify, deploy, and optimize digital twin solutions while collectively advancing the core technologies that power tomorrow’s digital transformation.
The Digital Twin Testbed Program implements DTC’s Composability Framework – utilizing the Business Maturity Model, Platform Stack Architecture, and Capabilities Periodic Table—alongside a capabilities-focused maturity assessment framework that incorporates the evaluation of Generative AI, multi-agent systems, and other advanced technologies.
“We’re excited to announce these innovative digital twin testbeds,” said Dan Isaacs, GM & CTO of the DTC. “We’re seeing strong interest from members worldwide in participating in our collaborative testbed program. Our members are already utilizing this program to develop further and adopt intelligent and generative digital twins and other enabling technologies.”
New DTC member-led testbeds include:
Virtual Twins for Smart Factory Innovation – In an era of intensifying competition, skills shortages, and unstable demand, the need for modernized production facilities has never been greater. The testbed highlights the importance of digital twins in virtually simulating production lines, driving innovation, reducing commissioning time, and leveraging operational data for continuous improvement. Dassault Systèmes leads this testbed.
“In an era of intensifying competition, skills shortages, and unstable demand, the need for modernized production facilities has never been greater. To stay ahead, companies must prioritize the integration of Digital Twins into their processes. This DTC testbed highlights the importance of leveraging Digital Twins to virtually simulate production lines, drive innovation, reduce commissioning time, and leverage operational data for continuous improvement“ comments Philippe DELANNOY, Industrial Equipment, Industry Business Value Consultant Director, Dassault Systèmes.
Cognitive Network Orchestration – This testbed validates the capability of agent-based digital twins to communicate across industrial and business domains using standardized manufacturing ontologies. It implements a digital twin-based multi-agency framework with operational infrastructure and communication protocols to create a network of intelligent agents that operate across organizational boundaries. XMPro leads this testbed with Microsoft.
“The DTC testbed program provides invaluable collaborative environments to validate emerging technologies in realistic settings. At XMPro, we’re committed to expanding the horizons of digital twins through multi-agent generative systems that operate across organizational boundaries. These industry-academic partnerships accelerate innovation and provide practical guidance that drives meaningful digital transformation across industries” comments Pieter van Schalkwyk – CEO XMPro.
Digital Twins for Metal 3D Printing and Optimization – The testbed addresses the demand for high-quality production of complex geometry metal alloy parts. It demonstrates an IoT-enabled, state-of-the-art 3D metal printer coupled with a digital twin development architecture to achieve real-time, closed-loop control and diagnostics/prognostics capabilities. This integration enhances manufacturing quality and interoperability, advancing industry knowledge in digital manufacturing. Rowan University and XMPro lead this testbed.
“The digital manufacturing testbed for flaw-free metals will serve as a collaborative academia-industry-government environment to evaluate the benefits of implementing digital twins in production-grade metal additive manufacturing methods. This technology is critical to advance high-quality production of advanced components by leveraging multimodal sensing coupled with physics-based and AI modeling to create fully automated control systems with additional diagnostics and prognostics capabilities” comments Prof. Antonios Kontsos, Director of the Digital Engineering Hub @ Rowan University and Professor of Mechanical Engineering.
For more information: www.digitaltwinconsortium.org
