Enabling new levels of automation, efficiency, and precision.
Leading industrial companies around the world are implementing NVIDIA technologies for large-scale AI initiatives. NVIDIA-accelerated computing makes it possible to deploy AI at industrial scale, letting you take advantage of vast amounts of sensor and operational data to optimize operations, improve time to insight, maximize yield, and reduce costs.
Explore what the Financial Times has to say about the new era of industrial digitalization, where manufacturers are turning to accelerated computing, GPUs, and specialized hardware and software to power dramatic performance and sustainability improvements.
Explore five real-world developer use cases, and access insights and resources to develop your own digital twin solutions.
Reinventing manufacturing—from design to delivery.
Designers, engineers, and analysts need to process massive models so they can innovate, iterate, and solve problems—all at the speed of light. Meanwhile, manufacturers need insights from vast amounts of sensor and operational data to optimize operations, improve time to insight, and reduce costs. NVIDIA-accelerated technology makes it all possible, at scale, from anywhere.
Enabling advances at sub-nanometer scale.
With the move to smaller technology nodes, the demand for compute cycles in electronic design automation (EDA) and semiconductor manufacturing is rapidly and exponentially increasing. Advanced chip manufacturing requires over 1,000 steps, producing features the size of a biomolecule. Each step must be nearly perfect to yield functional output. To meet this need, accelerated computing and AI have become critical to the semiconductor industry, addressing compute-intensive workloads like logic simulation and verification, physical design, computational lithography, and other mask shop and wafer fab workloads, including inspection and metrology.
Powering next-gen performance, manufacturability, and efficiency.
The commercial success of today’s aerospace industry is driven by product innovation, quality, reliability, and operational efficiency. Accelerated computing is accelerating design cycle times with robust tools for engineering design and simulation, while lowering the total cost of owning and operating high-performance computing (HPC) infrastructure.
Revolutionizing agriculture with AI.
By using NVIDIA technologies, farmers can analyze data from diverse sources—such as soil moisture sensors, weather forecasts, and satellite imagery—to make better decisions about crop management, irrigation, and pest control. NVIDIA's AI-powered solutions can also help farmers automate repetitive tasks, including monitoring crops, detecting plant diseases, and analyzing soil conditions. By improving efficiency and productivity, these resources ultimately help farmers increase crop yields and reduce waste, contributing to a more sustainable and profitable agriculture industry.
Driving end-to-end innovation.
NVIDIA’s automotive solutions offer the performance and scalability needed to design, visualize, and simulate the future of driving. Designers and engineers can create virtual showrooms and car configurators, develop in-vehicle AI assistants, and validate autonomous driving technology—all with NVIDIA AI, Omniverse™, and accelerated computing platforms.
Learn from the industrial leaders using AI to optimize processes, reduce risk, and trim costs.
Image courtesy of BMW Group.
The global transportation company is adopting NVIDIA IGX, the enterprise-ready platform for industrial edge computing, to improve railway operations, lower maintenance costs and reduce energy use.
Manufacturers like Autodesk, Continental, Pegatron, Rockwell Automation, Siemens and Wistron are embracing digitalization and virtual factories to unlock new possibilities from planning to operations.
Image courtesy of 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.
The next era of industrial digitalization has arrived. With NVIDIA Omniverse APIs on Microsoft Azure, organizations across industries and around the world can connect, collaborate and enhance their existing tools to create the next wave of AI-enabled digital twins.
— Andy Pratt, Corporate Vice President, Microsoft Emerging Technologies
Computational lithography, specifically optical proximity correction, or OPC, is pushing the boundaries of compute workloads for the most advanced chips. By collaborating with our partner NVIDIA to run Synopsys OPC software on the cuLitho platform, we massively accelerated performance from weeks to days! The team up of our two leading companies continues to force amazing advances in the industry.
— Aart de Geus, Chairman and CEO, Synopsys
With Omniverse APIs, Teamcenter X lets companies like HD Hyundai unify and visualize massive engineering data sets interactively and integrate generative AI to generate 3D objects or HDRI backgrounds to see their projects in context. The result is an ultra-intuitive, photoreal, physics-based digital twin that eliminates waste and errors, delivering huge savings in cost and time.
— Dr. Roland Busch, CEO, Siemens AG
A new blueprint for interactive virtual wind tunnels enables unprecedented computer-aided engineering exploration for Altair, Ansys, Cadence, Siemens, and more.
Toyota, Yaskawa, Seven & i Holdings, and Rikei introduce digital twins and industrial AI to shepherd the next wave of digitalization.
At the NVIDIA AI Summit in India, leading consulting partners and industrial manufacturers announced they are using NVIDIA Omniverse to virtually integrate next-gen factories.
Siemens
Siemens is advancing the path to net-zero manufacturing with NVIDIA accelerated computing.
Accenture is debuting NVIDIA NIM™ Agent Blueprint, combining NVIDIA Omniverse, Isaac and Metropolis software to build autonomous, robot-operated software-defined factories and facilities.
Learn about the AI and accelerated computing hardware, software, and networking solutions for industrial applications.
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.
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.
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Business leaders across industries are working with us to digitalize and transform their industrial processes. Discover how they are integrating and scaling digital twins and AI to optimize operations, reduce costs, and drive sustainability.
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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 will illustrate how the application can be easily applied to a variety of manufacturing use cases.
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