Why is the use of digital twins a must these days?
Increased efficiency
Prediction and optimization
Maintenance and servicing
Product development and improvement
Cost reduction
Flexibility and adaptability
Improving cooperation
Real-time monitoring
What options are available today?
3D modeling and simulation: The creation of precise 3D models of physical plants, products or processes is crucial for the development of a digital twin. These models enable simulations, analyses and tests in a virtual environment.
Sensors and IoT (Internet of Things): The integration of sensors into physical plants enables real-time monitoring of parameters such as temperature, pressure, vibration and more. This data is then transferred to the digital twin in real time, enabling precise analysis and monitoring.
Big data and analytics: Processing large amounts of data is crucial to the performance of digital twins. Advanced analytics tools allow insights to be extracted from the collected data, leading to informed decisions.
Artificial intelligence (AI) and machine learning: The use of AI and machine learning enables digital twins to learn from experience, recognize patterns and make predictions. This is particularly important for optimizing processes and predicting potential problems.
Augmented reality (AR) and virtual reality (VR): AR and VR allow users to interact with digital twins and visualize information in the real world. This is particularly useful for training, maintenance and inspections.
Blockchain technology: Blockchain can help ensure the integrity and security of data in the digital twin. This is important to ensure that the information provided is reliable and unaltered.
Cloud computing: The use of cloud platforms enables easy access to large computing power and storage capacity, which is crucial for processing and storing large amounts of data related to digital twins.
Edge computing: By moving data processing tasks closer to the point of data generation (edge), companies can react more quickly to information and implement latency-sensitive applications.
Interoperability: The development of standards and protocols to ensure interoperability between different digital twins is crucial. This enables the exchange of data and information between different systems and platforms.
BUILDING A DIGITAL TWIN: A MULTI-STAGE JOURNEY
Define the objective: First, you need to clearly define which physical object, process or system you want to replicate digitally. What is the main goal of the digital twin? Do you want to improve performance, optimize maintenance, increase security or something else?
Identify data sources: Identify all relevant data sources that provide information about the physical object or process. These can be sensors, IoT devices, historical data and other sources of information.
Implement sensors and IoT devices: If necessary, install sensors and IoT devices to collect real-time data. This data is crucial for updating the digital twin.
Collect and store data: Set up an infrastructure to store and process the collected data. This can be done in the cloud or on-premise, depending on the requirements.
Data processing and analysis: Use data analysis tools and algorithms to gain valuable insights from the raw data. This can include real-time analytics, predictive modeling and other techniques.
Modeling and simulation: Create a virtual model that represents the physical object or process. This model should use the data from the sensors to enable accurate replication. You can use simulation software to check the behavior of the digital twin.
Real-time integration: Ensure that the digital twin is updated in real time to reflect the current conditions of the physical object or process. This requires seamless integration of data sources and model.
Visualization and user interface: Develop a user-friendly interface that allows users to monitor, control and analyze the digital twin. This can include dashboards and visualizations.
Continuous improvement: The digital twin is not a static project. Requires continuous improvement and adaptation to keep pace with the changing conditions of the physical object or process.
Security and data protection: Ensure that appropriate security measures are implemented to protect the digital twin's data. This is particularly important as sensitive information is involved.
Scaling and expansion: Depending on the requirements and successes of the digital twin, you may consider scaling the project or expanding it to other areas.
What options are available?
GPU technology
NVIDIA is known for its advanced graphics processing units (GPUs). These powerful GPUs are often used in data centers to support complex calculations, simulations and visualizations for digital twins. The parallel processing capability of GPUs is particularly useful for demanding simulations and AI applications.
However, NVIDIA is not only a leader in the field of GPUs, but also in the field of platforms. With products such as NVIDIA Omniverse Enterprise and Omniverse, the company sets standards for 3D simulations and collaboration. The Jetson series successfully addresses the area of edge computing applications, while Fleet Command enables companies to effectively manage their GPU resources. This underlines the versatility and innovative strength that characterize NVIDIA not only as a GPU manufacturer, but also as a provider of comprehensive platform solutions.
NVIDIA OMNIVERSE™ ENTERPRISE
NVIDIA Omniverse™ Enterprise in NVIDIA® OVX™ enables accurate, AI-enabled virtual simulations that are synchronized with the real world in real time. Companies use these digital twins to design, simulate and optimize products, devices and processes before they go into production.
In the coming years, simulations will be increasingly used to develop products, improve the customer experience and increase operational efficiency. This will require Universal Scene Description (USD) and workflow solutions. Digital twins play a key role in this and are already in use in various organizations.
For best performance and scalability, four NVIDIA ConnectX®-6 Dx network adapters are integrated into each NVIDIA OVX server to enable real-time simulation interactions. The NVIDIA Spectrum-3 switch provides efficient data transfer and simplifies network management.
3D and CAD data can be easily integrated into Omniverse Enterprise to enable collaborative workflows with third-party applications. Visual Components, Autodesk Maya, Revit and others are part of this innovation.
NVIDIA Omniverse™ Enterprise and NVIDIA® OVX™ are the future of business development and innovation.
NVIDIA Omniverse: Collaborative 3D simulation and visualization
NVIDIA ISAAC SIM
NVIDIA Fleet Command™
Simulation software:
Visual Components is a software platform used in the manufacturing industry to create digital twins of factories. A digital twin is a virtual representation of a physical product, process or system. In terms of factories, this means that the software can create a virtual representation of the entire production plant.
Visual Components offers a variety of features that enable engineers and planners to digitally design, simulate and optimize factories. Here are some of the key features and functions of Visual Components:
3D modeling: the software allows users to create 3D models of factories that include all relevant physical components such as machines, conveyors, storage areas and workstations.
Simulation: By simulating production processes, users can virtually test the operation of the factory. This includes the optimization of production processes, resource utilization and the identification of bottlenecks.
Material flow analysis: The software offers tools for analyzing the material flow in the factory. This makes it possible to identify bottlenecks, optimize stock levels and increase the efficiency of production processes.
Real-time visualization: Users can visualize the digital twin in real time to see changes and optimizations immediately.
Robot programming: Visual Components also supports the programming of industrial robots. This is particularly important in factories that rely on automated processes.
Collision checking: The software checks for collisions between different components in the digital factory to avoid potential problems in the real world.
Data integration: Visual Components enables the integration of data from other systems to create realistic and accurate models.
Visual Components is used by various industries, including automotive manufacturing, electronics production, mechanical engineering and logistics. It helps companies optimize their manufacturing processes, reduce costs and increase efficiency before physical changes are made in the real world.
Essentials
Professional
Premium
VC Robotics OLP
NVIDIA Omniverse Connector
Hardware solutions:
NVIDIA OVX systems from Supermicro
NVIDIA OVX systems from Supermicro
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