Industrial AI

Industrial AI is the application of physical AI and other artificial intelligence technologies to optimize industrial processes with enhanced automation and improved decision-making using real-time industrial data and predictive analytics.

NVIDIA Omniverse, Isaac, and Metropolis bring the power of industrial digital twins to industrial warehouses to simulate, test, and optimize robotic fleets at scale.

Industrial artificial intelligence (AI) is a critical enabler of industrial automation, enhancing the ability of machines, systems, and processes to operate with minimal human intervention. By integrating generative AI and AI agents with robotics, IoT, and advanced analytics, companies can optimize operations, improve operational efficiency, and enhance decision-making across the supply chain within the industrial sector.

AI-powered automation enables real-time monitoring, predictive maintenance, and process optimization, reducing downtime and improving system performance throughout the entire lifecycle of industrial assets. Additionally, technologies like digital twins, virtual representations of physical systems, allow businesses to simulate and verify the performance of industrial AI models and applications in a real-time digital environment before deployment in real industrial systems and facilities.

Industrial AI helps organizations accelerate digital transformation, creating smarter, more adaptive manufacturing and logistics systems and driving efficiency and resilience in an increasingly complex industrial landscape.

By leveraging AI technologies, companies can enhance their industrial applications and optimize industrial processes, leading to improvements in product quality, profitability, and sustainability.

At the heart of the industrial AI revolution is physical AI or AI-enabled robotics, which will enable fully autonomous industrial facilities in the future. AI-enabled robots are increasingly being trained and tested in digital twins of industrial facilities, enabling them to perform complex tasks with precision and efficiency. This digitalization of industrial facilities enhances automation, further improving productivity and reducing the need for human intervention in hazardous environments.

Another key benefit of industrial AI is its ability to help enterprises analyze and gain insight from vast amounts of industrial data. This data-driven approach enables predictive analytics, which can foresee potential issues and prevent unplanned downtime. By predicting equipment failures and maintenance needs, companies can maintain continuous operations and reduce costly interruptions.

Moreover, industrial AI plays a vital role in quality control. By continuously monitoring production processes and identifying defects in real time, AI ensures that products meet high standards, enhancing product quality. This not only boosts customer satisfaction but also reduces waste and rework, contributing to overall profitability.

In terms of sustainability, industrial AI helps industries minimize their environmental footprint. By optimizing resource usage and energy consumption, AI-driven solutions promote more sustainable practices. This is particularly important as industries strive to meet regulatory requirements and societal expectations for greener operations.

KION Group and Accenture are testing, simulating, and optimizing multi-agent robot fleets in digital twin environment (View Demo).

Leading industrial and manufacturing companies are adopting industrial AI to enhance efficiency, reduce costs, and optimize workflows. From AI-powered warehouse robots to advanced manufacturing simulations, the industrial sector is undergoing a rapid transformation.

Siemens will use NVIDIA Omniverse^TM Cloud APIs with its Siemens Xcelerator platform, starting with cloud-based product lifecycle management (PLM) software, Teamcenter X. This integration will enable engineering teams to create more immersive and photorealistic digital twins, helping to eliminate workflow waste and reduce errors. The use of generative AI accelerates workflows such as applying materials and lighting environments in physically based renderings.

Siemens Industrial Copilot for Operations is a generative AI-powered assistant for shopfloor workers that uses a combination of NVIDIA Metropolis and NIM microservices This allows automation and maintenance engineers to make real-time queries about operational and document data in order to facilitate rapid decision-making and reduce machine downtime. The Siemens Electronics Factory in Erlangen, Germany, implemented the Copilot for Operations to help operators better understand machine error codes across its solder machines which is leading to a 30% increase in productivity.

KION Group and Accenture are integrating AI-enabled robots and digital twins to optimize warehouse operations and supply chains. By building solutions with the Mega NVIDIA Omniverse Blueprint, KION and Accenture can design, test, and optimize warehouse layouts and simulate and test robot fleets without disrupting real-world operations. These solutions enable their teams to improve the efficiency, safety, and adaptability of their warehouses. Automated forklifts, smart cameras, and other advanced robotic systems are simulated and validated within warehouse digital twins, helping to optimize facility layouts, robot fleet coordination, and worker allocation. KION plans to use vision language models to better understand carrier load status changes and anomalies. 

Delta Electronics, a global leader in power and thermal management technologies, has enhanced its smart manufacturing capabilities by developing a digital twin platform using NVIDIA Omniverse and Universal Scene Description (OpenUSD). This platform virtually links specific production lines, aggregating 3D data from diverse equipment to create comprehensive digital replicas of operations. 

By integrating NVIDIA Isaac Sim into their solutions, Delta developers can generate physically accurate, photorealistic synthetic data to train computer vision models and simulate the performance of inspection cameras. This approach allows Delta to optimize every aspect of the factory process before actual production begins, leading to reduced downtime and improved efficiency.

Delta Electronics is redefining production lines and industrial inspection with digital twins and synthetic data.

Wistron, a global technology service provider, is leveraging industrial AI technologies to accelerate the production of the NVIDIA GB200 Grace Blackwell product line. By building digital twins of its factories using Omniverse, Wistron can simulate and optimize production processes in a virtual environment. This allows for rapid iteration and refinement of manufacturing workflows, leading to improved production quality and reduced time-to-market. 

Additionally, Wistron has developed a heat-flow simulator based on physics-informed AI, capable of evaluating nearly 100 room layouts for the new product line in just one minute.

This technical collaboration has drastically reduced the end-to-end workflow, enabling Wistron to respond more quickly to the rapid iteration of AI server products and help ensure that new products can move from development to mass production in sync with market demand.

Foxconn, the world’s largest manufacturer, is accelerating the deployment of new production facilities for the NVIDIA Blackwell product line. By creating digital twins of factories, Foxconn can virtually integrate facility and equipment layouts, enabling optimization of floor plans and strategic placement of cameras to streamline operations. This virtual integration reduces costly real-world changes and enhances efficiency.

In the digital twins, Foxconn simulates and tests autonomous robots using solutions built on NVIDIA Isaac Sim, ensuring that industrial manipulators and autonomous mobile robots operate effectively before real-world deployment. Additionally, Foxconn employs NVIDIA Metropolis for its vision AI solutions, optimizing camera placements to monitor factory floors, thereby improving worker safety and operational oversight. The company anticipates significant cost savings and over a 30% annual reduction in energy consumption at its Mexico facility alone.

Continental, a leading German automotive technology company, has developed AI-powered virtual factory solutions aimed at enhancing manufacturing operations. Utilizing NVIDIA Omniverse and OpenUSD, they created two key applications:

ContiVerse: An immersive digital twin platform that provides real-time insights into factory processes and machinery. By aggregating data into a cloud-based data lake, ContiVerse enables engineers to simulate and optimize production lines, facilitating informed decision-making and rapid identification of issues. For instance, a full-scale digital twin of their Novi Sad, Serbia factory allows for virtual Gemba walks, enhancing remote monitoring and troubleshooting.

Industrial Co-Pilot: A virtual agent that combines generative AI with 3D visualization to assist factory teams in maintenance tasks. This tool, built in partnership with IT consulting firm SoftServe, streamlines maintenance processes by providing intuitive, visual guidance, thereby reducing downtime and increasing productivity.

By integrating these solutions, Continental anticipates a 10% reduction in maintenance efforts and downtime, leading to increased productivity across their manufacturing operations.

Pegatron has developed PEGAVERSE, an AI-enabled digital twin platform, to transform its manufacturing operations and improve efficiency, quality, and cost-effectiveness. Built using NVIDIA Omniverse, AI, and OpenUSD, PEGAVERSE allows engineers and factory managers to collaboratively plan, simulate, and optimize production lines with real-time insights into facilities, equipment, and maintenance tasks. The platform enables use cases such as predictive maintenance, process optimization, resource planning, remote monitoring, and quality control across virtual factories in Taiwan, India, Indonesia, China, and Vietnam.

PEGAVERSE integrates machine learning, generative AI, and IoT to enhance digital twin experiences. Pegatron's PEGAAi platform streamlines data collection, labeling, and model training, while large language models (LLMs) enable automation and flexibility in manufacturing processes. The company also employs solutions built on NVIDIA Isaac Sim for robot simulation and NVIDIA Metropolis for automated optical inspections, improving production accuracy. By adopting OpenUSD, Pegatron unifies disparate tools and data, accelerating design and simulation workflows. This digital transformation allows Pegatron to optimize factory operations, reduce downtime, and enhance manufacturing efficiency on a global scale.

Pegatron is also building video analytics AI agents to detect anomalies on the assembly line and further improve quality yields. Using the NVIDIA AI Blueprint for video search and summarization, Pegatron is able to analyze a nuanced 7-step assembly process and alert workers when differences are spotted compared to standard operating procedures. ​By fine-tuning the vision language model, Pegatron is seeing accuracy rates in the high 90s.