The Digital Twin paradigm can be applied to numerous real-world scenarios, but there is no one size fits all approach. Greenfield implementations of Digital Twins are rare, and practical Digital Twin solutions nearly always follow a step-by-step approach of integrations into existing processes, workflows, infrastructure, and software. For new Digital Twin initiatives, best practice is to start small, with a modular approach for each part of the Digital Twin workflow.

Digital Twin implementation and integration challenges are heavily dependent on the context and domain of the "twinned" physical real-world assets, which may only become apparent as development evolves, hence the need for flexible Digital Twin ecosystems.

This paper explored the practical implications and considerations for developing Digital Twin solutions using Dell PowerEdge R760xa servers and NVIDIA Omniverse Enterprise Platform as foundational building blocks.

We demonstrated:

• The ability to easily customize and assign hardware for various workflows, with accelerated compute and graphics.
• A virtualized deployment of the NVIDIA Omniverse Enterprise Platform.
• 3D Modeling Framework in a scenario simulation.
• Synthetic data generation with automatic image annotation and labeling.
• AI object detection model development:
  • Training and validation with SDG images
  • Model performance on real-world images

These demonstrations combine to offer the flexibility, interoperability, and collaborative capabilities needed to begin a Digital Twin journey with CV solutions.