Enabling new levels of automation, efficiency, and precision.
Leading industrial companies around the world are implementing NVIDIA technologies for large-scale AI initiatives. GPU-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 the five steps you need to take to get started with digital twins and get insight into what we’ve learned about successful digital twin initiatives.
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 GPU-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.
Semiconductor engineers show how a specialized industry can customize large language models with NVIDIA NeMo™ to gain an edge.
The automaker is bringing the power of industrial AI to its entire production network as part of its digital transformation.
Image courtesy of BMW Group.
The startup will deliver the first six of its NVIDIA® Jetson™-driven Founder Series MK-V tractors to leading wine, spirits, and beer producer Constellation Brands.
Image courtesy of Monarch Tractor.
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
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
The marriage of NVIDIA accelerated computing with Jetson edge AI on our Monarch MK-V has helped our customers reduce the use of unneeded herbicides with our cutting-edge, zero-emission tractor. This revolutionary technology is helping our planet’s soil, waterways, and biodiversity.
— Carlo Mondavi, Chief Farming Officer, Monarch Tractor
Virtual factory and autonomous vehicle simulation engines hosted on Microsoft Azure fast-track the design, building, and operation of cars.
Foxconn is integrating NVIDIA technologies to develop AI factories. This is a new class of data centers producing intelligence and powering a wide range of applications–including digitalization of manufacturing and a growing number of LLM generative AI services.
Image Courtesy of Foxconn.
Sweden’s Hexagon AB is connecting their reality capture and manufacturing platforms to NVIDIA Omniverse, so enterprises can more easily develop and deploy digital twin solutions.
Image courtesy of Hexagon.
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.
Featured
NVIDIA founder and CEO Jensen Huang outlines the role of accelerated computing and AI in his address to semiconductor industry leaders at ITF World 2023.
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 will illustrate how the application can be easily applied to a variety of manufacturing use cases.
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