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Nvidia Omniverse enlists top electronics makers to digitalize factories

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Nvidia announced at Computex that electronics manufacturers worldwide are using its Omniverse simulation and collaboration platform to improve their factories.

These industrial digitalization efforts are using a new, comprehensive reference workflow that combines NVIDIA technologies for generative AI, 3D collaboration, simulation and autonomous machines, said Deepu Talla, vice president of embedded and edge computing at Nvidia, in a press briefing.

“The case for industrial digitalization is very clear and it is here and it is real,” Talla said.

Supported by an expansive partner network, the workflow for Omniverse and the larger Nvidia ecosystem helps manufacturers plan, build, operate and optimize their factories, Talla said.


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The ecosystem includes Nvidia Omniverse, which is like a metaverse for engineers and connects top computer-aided design apps, as well as APIs and cutting-edge frameworks for generative AI. It also includes the Nvidia Isaac Sim application for simulating and testing robots; and the Nvidia Metropolis vision AI framework, which uses intelligent video analytics to automate cities. Metropolis is now enabled for automated optical inspection.

Each of these industries are humongous, multi-trillion-dollar industries — from automotive to healthcare, manufacturing, retail and telco — and all of them are racing to digitalization,” Talla said. “The promise of simulation has always been clear. It’s faster, cheaper and safer to do simulation. But the hcallenge has been whether you do it with the right fidelity.”

In his keynote address at Computex, Nvidia CEO Jensen Huang showcased a demo of an entirely digitalized smart factory — an industry first for electronics makers.

“The world’s largest industries make physical things. Building them digitally first can save enormous costs,” said Huang. “Nvidia makes it easy for electronics makers to build and operate virtual factories, digitalize their manufacturing and inspection workflows, and greatly improve quality and safety while reducing costly last-minute surprises and delays.”

World’s leading electronics makers embrace factory digitalization

Nvidia’s Metropolis for Factories is getting wide adoption.

The new reference workflow is being used by Foxconn Industrial Internet, Innodisk, Pegatron, Quanta and Wistron, as they work to optimize their workcell and assembly line operations while lowering production costs.

Foxconn Industrial Internet, a service arm of the world’s largest technology manufacturer, is working with Nvidia Metropolis ecosystem partners to automate significant portions of its circuit-board quality-assurance inspection points.

“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,” said Tai-Yu Chou, CTO at Foxconn Industrial Internet, in a statement. “The combination of Nvidia Metropolis for factories and Isaac Sim for robotics is helping us realize industrial automation goals faster than ever imagined.”

Innodisk is deploying Nvidia Metropolis to automate optical inspection processes on its production lines, saving cost and improving production efficiency.

Pegatron, a leading electronics manufacturer and service provider, is using the reference workflow to digitalize its circuit-board factories with simulation, robotics and automated production inspection.

“Nvidia Omniverse, Isaac Sim and Metropolis give us the ability to accomplish AI training, enhance factory workflows and run numerous simulations in the virtual world before we commit to an idea in the physical world,” said Andrew Hsiao, associate vice president of the software R&D division at Pegatron, in a statement. “Digitalizing our entire factory enables us to simulate the robotics and automation pipeline from end to end, and lets us try things out in a simulated environment, which saves time and greatly reduces costs.”

Quanta, a major manufacturer of laptops and other electronic hardware, is using AI robots from its subsidiary Techman Robot to inspect the quality of manufactured products. Techman is leveraging Isaac Sim to simulate, test and optimize its state-of-the-art collaborative robots while using Nvidia AI and GPUs for inference on the robots themselves.

Wistron, one of the world’s largest suppliers of information and communications products, is tapping Nvidia Omniverse to build digital twins of its automated receiving lines and operations buildings using inputs from Autodesk AutoCAD, Autodesk Revit and FlexSim.

Wistron also uses Nvidia Metropolis to automate portions of its circuit-board optical inspection using AI-enabled computer vision.

Industrial ecosystem using Nvidia tech

Nvidia is deploying Isaac AMR (autonomous mobile robots).

Nvidia is working with several manufacturing-tools and service providers to build a full-stack, single architecture with each at every workflow level.

At the systems level, Nvidia IGX Orin provides an all-in-one edge AI platform, combining industrial-grade hardware with enterprise-level software and support. IGX meets the unique durability and low-power-consumption requirements of edge computing, while delivering the high performance needed for developing and running AI applications.

Manufacturer partners Adlink, Advantech, Aetina, Dedicated Computing, Onyx, Prodrive Technologies and Yuan are developing IGX-powered systems to serve the industrial and medical markets. These systems allow the benefits of digitalization to be realized during physical production.

At the platform level, Omniverse connects the world’s leading 3D, simulation and generative AI providers. The open development platform, for example, lets teams build interoperability between their favorite applications — such as those from Adobe, Autodesk and Siemens.

Omniverse demo at Computex

A demo at the Computex keynote showcased Omniverse connected to various AI assistants, such as ChatGPT and Blender GPT, to simplify 3D workflows and Python-application development. Nvidia Omniverse Cloud, a platform-as-a-service now available on Microsoft Azure, gives enterprise customers access to the full-stack suite of Omniverse software applications, and Nvidia OVX infrastructure, with the scale and security of Azure cloud services.

And at the application level, Isaac Sim allows companies to build and optimally deploy AI-based robots. Manufacturers can work with industrial automation company Ready Robotics to program their robot tasks in simulation before deploying in the real world.

Simulation technology partners like SoftServe and FS Studio shorten development timelines for customers by building digital twin-based simulations.

“Even after the physical thing is built, it can constantly be updated and modified in simulation before it’s in the real world,” Talla said. “Nvidia Omniverse is a platform that is fundamentally built for industrial metaverse applications.”

Also at the application level, Nvidia Metropolis includes a collection of factory-automation AI workflows that enable industrial solution providers and manufacturers to develop, deploy and manage customized quality-control solutions that save cost and improve production throughput. A large partner ecosystem — including Adlink, Aetina, Deloitte, Quantiphi and Siemens — is helping to bring these solutions to market.

“Omniverse platform tools are used to create the digital version of a factory. In order to deploy any industrial factory, you need Omniverse on one side, and then you need the runtime, the AI model run time with Metropolis,” Talla said.

WPP partnership

WPP is using Omniverse to build ads remotely.
WPP is using Omniverse to build ads remotely.

In other news, Nvidia and digital advertising giant WPP announced they are developing a content engine that harnesses Nvidia Omniverse and AI to enable creative teams to produce high-quality commercial content faster, more efficiently and at scale while staying fully aligned with a client’s brand.

The new engine connects an ecosystem of 3D design, manufacturing and creative supply chain tools, including those from Adobe and Getty Images, letting WPP’s artists and designers integrate 3D content creation with generative AI. This enables their clients to reach consumers in highly personalized and engaging ways, while preserving the quality, accuracy and fidelity of their company’s brand identity, products and logos.

Huang unveiled the engine in a demo during his Computex keynote address, illustrating how clients can work with teams at WPP, the world’s largest marketing services organization, to make large volumes of brand advertising content such as images or videos and experiences like 3D product configurators more tailored and immersive.

“The world’s industries, including the $700 billion digital advertising industry, are racing to realize the benefits of AI,” Huang said. “With Omniverse Cloud and generative AI tools, “WPP is giving brands the ability to build and deploy product experiences and compelling content at a level of realism and scale never possible before.”

“Generative AI is changing the world of marketing at incredible speed,” said Mark Read, CEO of WPP, in a statement. “Our partnership with Nvidia gives WPP a unique competitive advantage through an AI solution that is available to clients nowhere else in the market today. This new technology will transform the way that brands create content for commercial use, and cements WPP’s position as the industry leader in the creative application of AI for the world’s top brands.”

Engine for creativity

Nvidia Isaac autonomous mobile robot can do inspections.

The new content engine has at its foundation Omniverse Cloud — a platform for connecting 3D tools, and developing and operating industrial digitalization applications. This allows WPP to seamlessly connect its supply chain of product-design data from software such as Adobe’s Substance 3D tools for 3D and immersive content creation, plus computer-aided design tools to create brand-accurate, photoreal digital twins of client products.

WPP uses responsibly trained generative AI tools and content from partners such as Adobe and Getty Images so its designers can create varied, high-fidelity images from text prompts and bring them into scenes. This includes Adobe Firefly, a family of creative generative AI models, and exclusive visual content from Getty Images created using NVIDIA Picasso, a foundry for custom generative AI models for visual design, the companies said.

With the final scenes, creative teams can render large volumes of brand-accurate, 2D images and videos for classic advertising, or publish interactive 3D product configurations to NVIDIA Graphics Delivery Network, a worldwide, graphics streaming network, for consumers to experience on any web device.

The new content engine will soon be available exclusively to WPP’s clients around the world.

Isaac mobile robots

Isaac AMR is moving into early access with customers.
Nvidia Isaac AMR is moving into early access with customers.

Nvidia also announced that it has brought advanced autonomy to mobile robots using the Isaac robotics platform.

Isaac autonomous mobile robot (AMR) is moving into early access with customers, and Nova Orin-based reference robots are becoming available for evaluation.

Mobile robot shipments are surging to meet the growing demands of industries seeking operational efficiencies, NVIDIA is launching a new platform to enable the next generation of autonomous mobile robot (AMR) fleets, Nvidia said.

Isaac AMR brings advanced mapping, autonomy and simulation to mobile robots and will soon be available for early customers, Huang announced during his keynote address at the Computex technology conference in Taipei.

Isaac AMR is a platform to simulate, validate, deploy, optimize and manage fleets of autonomous mobile robots. It includes edge-to-cloud software services, computing and a set of reference sensors and robot hardware to accelerate the development and deployment of AMRs, reducing costs and time to market.

Mobile robot shipments are expected to climb from 251,000 units in 2023 to 1.6 million by 2028, with revenue forecast to jump from $12.6 billion to $64.5 billion in the period, according to ABI Research.

Despite the explosive adoption of robots, the intralogistics industry faces challenges. Traditionally, software applications for autonomous navigation are often coded from scratch for each robot, making rolling out autonomy across different robots more complex.

Also, warehouses, factories and fulfillment centers are enormous, frequently running a million square
feet or more, making them hard to map for robots and keep updated. And integrating AMRs into existing workflows, fleet management and warehouse management systems can be complicated.

For those working in advanced robotics and seeking to migrate traditional forklifts or automated guided vehicles to fully autonomous mobile robots, Isaac AMR provides the blueprint to accelerate the migration to full autonomy, reducing costs and speeding the deployment of AMRs.

Isaac AMR is built on the foundations of the Nvidia Nova Orin reference architecture. Nova Orin is the brains and eyes of Isaac AMR. It integrates multiple sensors including stereo cameras, fisheye cameras, 2D and 3D lidars with the powerful Nvidia Jetson AGX Orin system-on-module. The reference robot hardware comes with Nova Orin pre-integrated, making it easy for developers to evaluate Isaac AMR in their own environments.

Quanta’s Techman Robot selects Isaac Sim for inspections

Taiwan’s Quanta is using cobots to accelerate robotics-based inspection by 20%.

Nvidia said Taiwan’s robot firm Techman Robot selected Isaac Sim to optimize automated optical inspections.

The firm said it accelerated robotics-based inspection by 20% to improve electronics manufacturing product quality with Isaac Sim on Omniverse.

Huang said that electronics manufacturer Quanta is using AI-enabled robots to inspect the quality of its products. Techman Robot is using Isaac to develop a custom digital twin application to improve inspection on the Taiwan-based electronics provider’s manufacturing line.

The demo showed how Techman uses Isaac Sim to optimize the inspection of robots by robots on the manufacturing line. In effect, it’s robots building robots.

Automated optical inspection, or AOI, helps manufacturers more quickly identify defects and deliver high-quality products to their customers around the globe. The Nvidia Metropolis vision AI framework, now enabled for AOI, is also used to optimize inspection workflows for products ranging from automobiles to circuit boards.

Techman developed AOI with its factory-floor robots by using Isaac Sim to simulate, test and optimize its collaborative robots, or cobots, while using Nvidia AI and GPUs for training in the cloud and inference on the robots themselves.

Isaac Sim is built on Omniverse — a development platform for building and operating industrial metaverse applications.

Taiwan’s electronics firms adopt Nvidia Metropolis for Factories

Nvidia’s Metropolis for Factories is being used to digitalize factories in Taiwan.

Taiwan’s electronics firms are also buying into Nvidia Metropolis for Factories.

The $46 trillion global electronics manufacturing industry spans more than 10 million factories worldwide, where much is at stake in producing defect-free products. And more than 50 leading electronics manufacturers are adopting Nvidia Metropolis for Factories, Nvidia said.

Foxconn, Pegatron, Quanta, Siemens, Wistron and others are implementing Metropolis for Factories, Huang announced during Computex.

Metropolis for Factories is a collection of factory automation workflows that enables industrial technology companies and manufacturers to develop, deploy and manage customized quality-control systems that offer a competitive advantage.

Manufacturers globally spend more than $6 trillion a year in pursuit of quality control, and they apply defect detection on nearly every product line. But manual inspections can’t keep up with the demands.

Many manufacturers have automated optical inspection (AOI) systems that can help, but often these have high false detection rates, requiring labor-intensive and costly secondary manual inspections in an already challenging labor market, reducing their value.

Nvidia Metropolis for Factories now offers an AI platform and workflows for the development of incredibly accurate inspection applications such as AOI.

Manufacturer Pegatron, based in Taipei’s Beitou district, is using Nvidia Metropolis for Factories on its production lines. Pegatron manufactures everything from motherboards to smartphones, laptops and game consoles.

With a dozen manufacturing facilities handling more than 300 products and more than 5,000 parts per day, Pegatron has a lot of quality control to manage across its product portfolio. Further, frequent product updates require ongoing revisions to its AOI systems.

Pegatron is using the entire Metropolis for Factories workflow to support its printed circuit board (PCB) factories with simulation, robotics and automated production inspection. Metropolis for Factories enables the electronics manufacturing giant to quickly update its defect detection models and achieve 99.8% accuracy on its AOI systems, starting with small datasets.

Pegatron also uses Nvidia Isaac Sim, a robotic simulator, to program robotic arms in simulation and
to model the performance of its fleets of mobile robots. Tapping into Omniverse Replicator provides synthetic data generation to simulate defects, helping build massive training datasets with domain randomization and other techniques.

In Metropolis, the Nvidia TAO Toolkit allows Pegatron to access pretrained models and transfer learning to build its highly accurate defect detection models from its enhanced datasets. The Nvidia DeepStream software development kit can be used to develop optimized intelligent video applications that handle multiple video, image and audio streams. Using DeepStream, Pegatron was able to achieve a 10 times improvement in throughput.

Moreover, Omniverse enables Pegatron to run digital twins of its inspection equipment, so it can simulate future inspection processes, promising increased efficiencies to its production workflow.

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