NVIDIA Aims to Enhance Manufacturing Automation With AI, Cloud, and Digitization
AI-driven technology has recently experienced a huge influx of new users and technological advancements. NVIDIA has added new digital infrastructure to help end users realize some of its benefits.
Recent trends involving nearly every sector of manufacturers and end users have drastically shifted automation operations, involving more and more cutting-edge technology, from AI to edge computing and digitalization.
Projections of different automation fields show vast amounts of growth within the industry, for example, with AMR sales expected to increase from 251,000 units in 2023 to 1.6 million in the next five years. With such large increases in automation itself, computational technology enhancements are likely to grow at similar rates as well.
NVIDIA Enhances Digital Simulation and AI Technology
NVIDIA, a pioneer in accelerated computing, has been working to implement AI technology into several new products for its customers. NVIDIA Metropolis, Omniverse, Isaac AMR, and Isaac SIM have been developed to help companies adopt new technology into their plants to help with increasing efficiency, reducing downtime, and automating of new processes. Each new product helps end users take advantage of AI and digital twin technology.
Digital twins can be used to speed up deployment and solve problems before they happen. Image used courtesy of NVIDIA
NVIDIA Metropolis
The global electronics industry is worth nearly $46 trillion. Defects in products can mean large losses for manufacturers, so product quality is a significant part of the electronics manufacturing industry. NVIDIA Metropolis is designed to help manufacturers with the design, development, and implementation of quality control systems.
Pegatron, a leading electronics manufacturer, has recently implemented the technology to help with simulation, robotics, and automated production inspection. The adoption has led the company to obtain a 99.8% accuracy on their automated optical inspection (AOI) systems.
AMRs can greatly benefit from using AI for guidance and mapping. Image used courtesy of Adobe Stock
NVIDIA Omniverse
NVIDIA Omniverse is a tool that allows manufacturers to power industrial digitalization. The tool is AI-augmented, helping manufacturers create digital simulations without 3D data silos. It can help with the building of a digital manufacturing metaverse with little to no code by using AI-generated data. The use of metaverse operations allows customers to simulate and try different ideas before implementing them in the real world, saving both time and money.
NVIDIA Isaac AMR
With the recent rise in AMR use, NVIDIA has developed new technology to help with the implementation of autonomous mobile robot fleets. Isaac AMR gives end users access to advanced mapping capabilities and simulation technology.
AMR implementation can be a challenge because of programming needs associated with the mapping of large areas. With advanced AI-generated mapping, this problem can largely be eliminated, especially when infrastructure changes. It can also aid in the implementation of initial installation and use of AMRs in plants that have never used them before.
NVIDIA Isaac SIM
The NVIDIA Isaac SIM is an AI-based scalable robotics simulation that allows users to develop, simulate and test AI-based robotic systems in a virtual realm. The synthetic data generation tool is capable of helping provide photorealistic, physically accurate virtual environments for accurate robotic simulation. The simulation tool comes with people simulation, CuOpt for AMR optimization, RTX Lidar Models for 3D perception, and an ROS (robot operating system) developer ecosystem.
Digitalization transforms processes (manufacturing, energy production, etc) by collecting data and creating accurate models of real-world behavior. Image used courtesy of Adobe Stock
AI, Cloud Computing, and Digitalization
The use of AI, cloud computing, and digital infrastructure has the possibility to save large amounts of money for manufacturers, but a lot of the technology is still in its infancy. Manufacturers should look at each individual application to weigh the pros and cons of implementing such technology because it is unlikely to be a one-size-fits-all, especially at this stage in the game.
