Factories worldwide are seeing notable change as industry leaders turn to NVIDIA’s Omniverse platform to create virtual replicas, or digital twins, of their manufacturing processes. In an effort to address labor shortages and improve operational efficiency, companies like Siemens, Foxconn, Wistron, and Caterpillar, among others, have incorporated NVIDIA’s technology into their workflows. These partnerships not only focus on simulation and planning, but also real-time monitoring and safety within factory and warehouse settings. Businesses are increasingly viewing digital twins as essential tools for enhancing decision-making and optimizing complex operations.
Global interest in digital twin and robotics simulation has steadily increased as industrial companies seek to modernize and automate workflows. In past developments, digital twins were mainly used for basic visualization and light simulation. The newest deployments using NVIDIA Omniverse, IGX Thor robotics processor, and Isaac platforms emphasize real-time AI at the edge, deeper integration with existing manufacturing software, and broader enterprise adoption. This marks a shift from earlier technology implementations, pushing toward more comprehensive and dynamic factory models now able to simulate full production lines, supply chains, and robotics systems.
How Are Major Firms Leveraging Omniverse?
Leading technology and manufacturing companies have embraced Omniverse and related NVIDIA products for multiple functions. Siemens is beta testing a digital twin toolkit within its Siemens Xcelerator platform, aimed at producing accurate 3D factory models enriched with live data streams. Foxconn, FANUC, and Wistron have begun implementing OpenUSD-based digital twins, making it easier for engineers to virtually assemble and optimize production lines. Foxconn, for example, is using Omniverse to simulate the layout of a large Houston facility dedicated to artificial intelligence hardware manufacturing. According to NVIDIA,
“Built for the AI era, this technology stack enables comprehensive simulation, optimization, and real-time performance monitoring that can help design smarter and more efficient factories, products, and data centers.”
Which Industries Benefit from Digital Twin Simulation?
NVIDIA’s industrial customers extend across automotive, electronics, heavy machinery, and chip manufacturing sectors. Companies such as Caterpillar, Lucid Motors, and Toyota apply Omniverse to model and optimize their factories’ infrastructure and supply chains before physical alterations take place. Belden has adopted the platform to build real-time safety and quality inspection systems, incorporating AI-driven hazard monitoring. Meanwhile, TSMC is accelerating chip fab construction and robotics integration using both Omniverse and the NVIDIA Isaac platform. These applications generally improve resource allocation, safety compliance, predictive maintenance, and workflow automation within large industrial environments.
How Is Robotics Development Changing with NVIDIA Platforms?
Robotics companies and divisions, including Figure, Amazon Robotics, and Agility Robotics, have partnered with NVIDIA to enhance the capabilities of their humanoid and mobile systems. New processors such as IGX Thor bring advanced AI directly to the edge, facilitating faster reinforcement learning and safer autonomous operations. Agility’s Digit robot, for example, uses the Jetson AGX Thor module for real-time perception and adaptability to dynamic logistics environments. Amazon’s robotics teams have shortened prototype-to-production timelines for systems like the BlueJay manipulator through the use of accelerated simulation training. Jensen Huang, CEO of NVIDIA, stated,
“Together with America’s manufacturing leaders, we’re building physical AI, Omniverse digital twins, and collaborative robots that will drive productivity, resilience, and competitiveness across the U.S. industrial base.”
Growing adoption of real-time digital twins and simulation tools points to evolving trends in manufacturing and robotics, driven by the versatility of platforms like NVIDIA Omniverse. Unlike previous digital manufacturing efforts that primarily involved offline simulation or partial automation, the current era emphasizes live data integration, scalable robotics training, and safe, human-centric factory design. Companies utilizing these tools are positioned to refine production with fewer physical prototypes, reduce downtime, and adapt quickly to labor or supply chain disruptions. For organizations integrating AI, digital twins facilitate not only resource optimization but also continuous improvement, serving both immediate and long-term productivity goals. Exploring solutions from both new and established vendors—and considering how these might support customization and interoperability—can assist businesses seeking to implement smart manufacturing initiatives effectively.
