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Harness breakthroughs in design, rendering, simulation, production, remote collaboration, and visualization to revolutionize product development, transform engineering, and power the factory of the future.
Explore the five steps you need to take to get started with digital twins and get insight into successful digital twin initiatives.
Learn how top CAE applications running on GPUs are speeding up simulations by 5X or more while lowering costs and energy consumption.
Transform product development workflows.
From conceptual design to marketing asset creation, NVIDIA technology enables designers and engineers to create stunning 3D designs and immersive, real-time, physically accurate visualizations with photorealistic renderings, accelerate design iterations, and bring amazing products to life exactly as envisioned.
Accelerate computer-aided engineering workflows.
NVIDIA’s GPU acceleration technology provides a wide array of solutions for analyzing and solving complex problems in structural mechanics (FEA), computational fluid dynamics (CFD), computational electromagnetics (CEM) and discrete element modeling (DEM). With NVIDIA, designers, engineers, and simulation experts can rapidly accelerate their CAE workflows and achieve efficient, effective results.
Boost factory agility, efficiency, and productivity.
The world’s leading manufacturers are using NVIDIA technology to infuse AI into every aspect of production, delivering higher-quality products and improving profit margins. Industrial digital twins—true-to-reality digital representations of factories—use a combination of AI, physics, real-time data from IoT devices, and insights from maintenance and design records. Digital twin simulations can drive precise factory planning, safety improvements, agility, and flexible factory design. In the physical factory, AI can power automation, robotics systems, quality inspection and testing, and predictive maintenance to eliminate waste from production. Finally, generative AI powered by large language models (LLMs) can support information availability and collaboration to improve operational productivity, equipment upkeep, and issue resolution.
Learn from manufacturers using AI and accelerated computing to optimize processes, reduce risk, and trim costs.
Slalom, Inc.
Kawasaki Heavy Industries, Ltd. (Kawasaki) is a manufacturing company that's been building large machinery for more than a hundred years. With NVIDIA cuOpt™ and NVIDIA Jetson™ Orin, Kawasaki partnered with Slalom, Inc. to transform its track maintenance and inspection capabilities.
Delta Electronics
Delta Electronics optimizes every part of the factory process before actual production starts using NVIDIA Omniverse™ and the NVIDIA Isaac Sim™ simulation application.
BMW Group
With NVIDIA Omniverse, the automaker is bringing the power of industrial AI to its entire production network as part of its digital transformation.
NVIDIA’s strength in AI and its strong ecosystem of application partners are providing Foxconn Industrial Internet with a path to significant operational efficiency gains. The combination of NVIDIA Metropolis for factories and Isaac Sim for robotics is helping us realize industrial automation goals faster than ever imagined.
— Tai-Yu Chou, CTO, Foxconn Industrial Internet
Ansys, Cadence, Hexagon, Microsoft, Rockwell Automation, Siemens, and Trimble adopt Omniverse technologies to help customers design, simulate, build, and operate physically based digital twins.
The robotics platform is adding new foundation models, a robot learning framework, and AI workflow orchestration and robot perception tools.
Siemens
Siemens to use NVIDIA Omniverse Cloud APIs with the Siemens Xcelerator platform to offer immersive visualization that enhances product lifecycle management.
Learn about the AI and high-performance computing (HPC) hardware, software, and networking solutions for manufacturing.
HPC and AI enable new levels of collaboration and efficiency in product design, engineering, simulation, and prototyping. Digital twins optimize design and operational flow in factories, warehouses, and distribution centers. Accelerated data science unlocks deeper insights for intelligent forecasting and decision-making. And technician dispatch and vehicle routing can be dynamically optimized to improve efficiency. These reduced operational burdens improve the ease of future expansions and relocations.
Automation is creating new levels of speed and accuracy in industrial environments. Robotic systems automate manufacturing, assembly, and material handling. Predictive maintenance and prognostics minimize downtime and maximize the life of equipment. And quality and throughput are increased with computer vision-enabled inspection, productivity inspection, and bottleneck analysis.
Worker safety and waste reduction are important considerations for industrial companies around the world. AI sensors and proactive alerts are being used to enhance functional safety, and digital twins are helping to model and improve worker ergonomics. Machine learning optimizes plant energy consumption, increases farming efficiency, decreases negative environmental impact, and helps develop clean energy systems.
Featured
In the age of AI, new manufacturing factory projects are going digital-first. Running real-time digital twin simulations—virtually optimizing layouts, robotics, and logistics systems years before the factory opens—is the future. See the official virtual opening of BMW Group’s new electric vehicle plant, opening in Debrecen, Hungary, in 2025.
Videos
Learn how to identify anomalies and failures in time-series data by using AI to estimate the condition of equipment and predict when maintenance should be performed.
Learn how to create an end-to-end hardware-accelerated industrial inspection pipeline to automate defect detection. Using NVIDIA’s own production dataset as an example, we'll illustrate how the application can be easily applied to a variety of manufacturing use cases.
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