Omniverse Platform#

The following shows the workflow for a Factory Digital Twin utilizing the Omniverse platform. This architectural diagram integrates key components at a category level, encompassing 3D model ingestion, data integration, real-time simulation, and feedback mechanisms. It illustrates the flow of data from geometric and USD models into the Digital Twin. Additionally, it outlines how IoT devices can be connected through extensions and services, becoming part of a customizable kit application that enhances data collection and operational insights. By leveraging Omniverse’s capabilities, the architecture ensures precise and dynamic simulations, enabling real-time monitoring and predictive analytics. This workflow underscores the importance of data accuracy, integration, and continuous optimization, providing a comprehensive and secure digital twin solution for modern manufacturing environments.

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Kit App Template#

  • Kit App Repository which is designed to be used for any Kit SDK based development. The Omniverse development platform provides the Kit SDK for developing Applications, Extensions, and Services.

  • Kit App Template is a single .kit file. These modules can state each other as dependencies to combine small capabilities into a greater whole providing complex solutions. Applications developed on Omniverse can be simply a collection of Extensions. By configuring these collections, you can create high-performance, custom solutions suited to your organization’s needs without necessarily writing any code. The kit-app-template enables developers to create cross-platform (Windows and Linux) accelerated applications, equipped with tooling to streamline packaging for easier deployment. This covers a broad range of use cases, from simulating real-world systems to generating photorealistic synthetic data for AI training. Whether your focus is on creating engaging virtual worlds, developing tools for data analysis, or crafting simulations, the combination of this repository and the Kit SDK provides the foundation you need.

  • Extension Template is defined by a .toml file and most commonly has a set of directories with Python or C++ code.

3D Models#

  • Firstly, geometry-based 3D models are developed using precise measurements and CAD (Computer-Aided Design) tools. The geometry-based 3D models are imported into the USD framework, which facilitates their integration and organization within the Digital Twin.

  • Once integrated, the Digital Twin leverages these 3D models to simulate real-world conditions and processes accurately. It enables detailed visualizations, predictive analyses, and real-time monitoring, providing a holistic view of the factory’s operations.

Extension Creation#

  • Extensions are a common development path within Omniverse and they serve as the fundamental building blocks of Applications and Services. In effect, all user-facing elements in an application developed on Omniverse are created using Extensions. Extensions such as the Content Browser, Viewport and Stage elements are used by the Omniverse USD Composer and Omniverse USD Presenter sample applications among many others. Extensions are persistent within Applications so long as they are configured as an application dependency or they are set to load in the Extension Manager.

  • Omniverse offers a Services framework based on its foundational Kit SDK. This framework is designed to simplify the construction of Services that can leverage the capabilities of custom Extensions. Developers can choose to run their Services in various settings, such as local machines, virtual machines, or in the cloud. The framework is flexible, allowing Services to be migrated to different infrastructures easily without changing the Service’s code. The framework promotes loose coupling, with its components serving as building blocks that foster scalability and resilience. These reusable components help accelerate the development of your tools and features for databases, logging, metrics collection, and progress monitoring. Creating a Service project employs the same tools used for Extensions, with a similar development process. However, certain aspects, such as configuration and dependencies, are unique to Services.

  • Extension Library: Kit SDK contains hundreds of Extensions providing runtime functionality such as USD, rendering, and physics - and other Extensions providing workflow solutions such as USD Stage inspectors, viewport, and content browsers. Virtually all user-facing elements in an Omniverse sample Application, such as Omniverse USD Composer or Omniverse USD Presenter, are created using Extensions. The very same extensions used in Omniverse sample Applications are also available to you for your own development. The number of extensions provided by both the Community and NVIDIA is continually growing to support new features and use cases. However, a core set of extensions is provided alongside the Omniverse Kit SDK.

  • App Streaming Extensions: Streaming interactive content to Users is an essential experience of any modern workflow, and Omniverse comes with a number of options out-of-the-box. All technologies make it possible to stream the content of a Kit-based application (Omniverse Kit, Omniverse Create, Omniverse Machinima, etc.) to other devices and platforms. This makes it possible to provide access to Omniverse features to a wide variety of devices, where it would otherwise not have been able to install Omniverse. Remotely accessing these features enables shared experiences for applications, and can be used for cases such as:

    • Accessing Omniverse from phones or tablets

    • Sharing access to hardware resources with a group of Users

    • Offering live production workflows on the Cloud

AI#

  • By simulating various scenarios and conditions, the Digital Twin creates a diverse set of synthetic data that mirrors potential real-world situations. This synthetic data encompasses a wide range of variables, including machine performance, environmental factors, and operational anomalies, providing a comprehensive dataset that might not be feasible to collect solely from the real world.

  • This synthetic data is then combined with real data collected from IoT devices, sensors, and robotic systems within the factory. The amalgamation of synthetic and real data results in a robust and diverse dataset, crucial for training sophisticated AI models. The AI models learn to recognize patterns, predict outcomes, and make decisions based on this enriched dataset.

  • Once trained, these AI models are integrated into the robots, enhancing their capabilities and decision-making processes. The feedback loop continues as the robots’ performance generates new data, which is fed back into the Digital Twin and AI systems, perpetually refining the models and optimizing the entire manufacturing process.

ERP (Enterprise Resource Planning)#

  • IoT devices installed in machinery and equipment continuously collect data on performance, efficiency, and operational status. This data is transmitted to the ERP system, providing real-time insights into the factory floor.

  • Robotic systems, equipped with sensors and connected to the network, also generate data on their activities, maintenance needs, and productivity metrics. This information is fed into the ERP, ensuring that the system has a comprehensive view of the production process.

  • A Digital Twin factory, a virtual replica of the physical factory, simulates processes and predicts outcomes based on the data received from IoT devices and robotic systems. The Digital Twin analyzes this data, offering valuable predictions and optimization suggestions, which are then integrated back into the ERP system.

Conclusion#

NVIDIA Omniverse offers a robust platform for developing and deploying high-performance 3D applications, extensions, and services. The Kit App Template allows developers to create custom solutions by combining extensions, which are building blocks defined by .toml files with Python or C++ code.

The Kit SDK includes hundreds of extensions for various functionalities, such as USD, rendering, and physics, supporting the development of tailored applications. Geometry-based 3D models are integrated into the USD framework to create Digital Twins, enabling detailed visualizations and real-time monitoring.

Omniverse supports AI and ERP integration by generating synthetic data from Digital Twins and combining it with real data from IoT devices. This data trains AI models to improve machine performance and decision-making, while the ERP system provides real-time insights and optimizes processes.

In summary, NVIDIA Omniverse is a powerful platform for developing 3D applications, enabling immersive VR/AR experiences, and integrating AI and ERP systems to enhance industrial operations.