Digital Twins

If you build products you should be using Digital Twins. Streamline product development, enhance quality, reduce costs, and accelerate time to market. Harness the power of NVIDIA's Omniverse Platform to make this a reality.
assembly digital twin

If You Build Products,
You Should Be Using Digital Twins

Moving from concept to market faster than your competitors is one of the hallmarks of a successful, sustainable product development strategy.

Digital twins are proving to have an oversized impact on businesses using them to curate data from multiple sources and activate it to improve outcomes at every step through design, manufacturing, and support.

Value

Digital twins provide a dynamic, virtual replica of physical assets or systems, enabling real-time monitoring, simulation, and optimization.

Predictive Maintenance

IoT sensors generate big data in real time that is analyzed in real-time to identify problems. This ability enables businesses to effectively predict maintenance, improving production line efficiency and lowering maintenance costs.

Realtime Monitoring

It’s difficult or even impossible to get a real-time, in-depth view of large systems. However, a twin can be accessed anywhere, enabling users to monitor and control the system performance remotely.

Data backed decision making

The availability of a large amount of real-time data and advanced analytics enables businesses to make better and faster decisions about whether or not, adjustments to a manufacturing value chain are financially sound.

Improved Team collaboration.

Process automation and 24/7 access to system information allow technicians to focus more on inter-team collaboration, improving productivity and operational efficiency.

Addressing Challenges

The concept of digital twins, a digital replica of a physical asset, process, or system, is transforming industries worldwide. However, like any new technology, implementing digital twins presents certain challenges for organizations

Access to Technical Expertise

Creating and managing digital twins requires a high level of technical expertise. Many organizations are struggling with a lack of in-house knowledge or skills in this area. Nebul provides access to specific expertise directly or through its partner network:

  1. On-Demand Experts: Nebul maintains a team of professionals with deep expertise in High Performance Computing (HPC), Nvidia Omniverse and AI/ML technologies. These experts are available to assist customers with every stage of their journey, from initial planning to ongoing support after launch.
  2. Partnerships: Nebul collaborates with various technology and industry partners (Nvidia, Autodesk, Dassault Systems, and others) to broaden the range of expertise available to customers.
  3. Knowledge Sharing: Nebul promotes a culture of knowledge sharing, encouraging its experts to disseminate their insights and experience both internally and with customers.

By providing access to a diverse array of expertise, Nebul helps its customers successfully implement and utilize advanced technologies, driving innovation and competitive advantage in their industries.

 

Selecting the right platform

Choosing the right platform for implementing Digital Twin solutions is a crucial decision for any company. Enterprise HPC leverages Nvidia Omniverse as it offers a compelling suite of features that cater to businesses of all sizes. Here are some factors to consider selecting the right platform:

  1. Realism & Accuracy: One of the key aspects of a successful digital twin is its ability to accurately mimic the physical counterpart. Nvidia Omniverse provides high-fidelity, physics-based simulations that can accurately mirror the real-world environment, which is crucial for realistic modeling and predictions.
  2. Interoperability: A key feature of Nvidia Omniverse is its emphasis on interoperability. It supports a wide variety of 3D design software and tools, making it easy to integrate into existing workflows. This allows for a seamless transition and reduces the friction associated with implementing new technologies.
  3. Collaboration Features: Nvidia Omniverse is built with collaboration in mind, allowing teams to work together in real time, regardless of their geographical location. This feature is crucial in today’s increasingly remote and distributed work environments.
  4. Powerful Computing Capabilities: Given that digital twins can be data-heavy and require significant computing power, Nvidia Omniverse leverages GPU-accelerated computing to manage these demands effectively, enabling real-time simulations and analyses.
  5. Support and Training: Nebul provides strong support and extensive training resources, helping your team to get up to speed quickly with the Omniverse platform.
  6. Data Security and Compliance: Nebul Enterprise HPC can be delivered on-premises, in your data center, and from the (sovereign) Nebul Cloud. This ensures that all data handled in the creation and management of digital twins adhere to necessary data privacy and compliance regulations.
  7. Scalability: As your business grows and evolves, so too will your digital twin needs. Nvidia Omniverse is designed to be highly scalable, allowing for growth and adaptability over time. It’s important to choose a platform that can evolve with your needs.

Choosing the right digital twin solution brings together the benefits of state-of-the-art technology, advanced features, and expert guidance, giving you a robust platform that can efficiently meet your business needs.

 

Data Collection and Management

Data collection is a fundamental part of creating and maintaining digital twins. The digital twin is essentially a data-driven model, simulating the behavior of its real-world counterpart based on the data it collects. Here are key points we take into consideration building digital twins:

  1. Real-Time Data: One of the key strengths of digital twins is their ability to process real-time data from various sources. This might include sensor data, operational data, or any other form of data that provides insight into the state and behavior of the physical entity.
  2. Data Quality: The accuracy and effectiveness of a digital twin heavily rely on the quality of data collected. High-quality data ensures that the digital twin can effectively mimic its real-world counterpart and make accurate predictions. Implementing quality controls in data collection is therefore essential.
  3. Data Integration: In many cases, the data for digital twins come from a variety of sources and may be in different formats. Effective data integration techniques are crucial to aggregate, organize, and prepare this data for use in the digital twin.
  4. Privacy and Security: Since digital twins often deal with sensitive operational data, privacy, and security measures must be implemented to protect this data during collection, transmission, and storage.
  5. IoT Devices: Internet of Things (IoT) devices are often used to collect data from the physical entity, especially in cases like industrial machinery or infrastructure. These devices need to be reliable, secure, and capable of transmitting data effectively.
  6. Continuous Collection: Digital twins require ongoing data collection to keep the model up-to-date. This continuous collection allows the digital twin to adapt to changes and provide real-time insights.
  7. Scalability: As the digital twin evolves and grows, the volume of data collected will also increase.

By understanding these aspects of data collection we can build more effective digital twins that you can use to gain better insights and make more informed decisions.

 

Integration with Existing Systems

Integration between your Digital Twin powered by Nvidia Omniverse and other systems such as Autodesk or back-office systems like ERP and CRM, is crucial for achieving a comprehensive view of your business operations and enabling efficient workflows. Here are some key points regarding this integration:

  1. Data Synchronization: Autodesk tools are widely used for creating 3D models and designs, which can be imported into Omniverse to create or update digital twins. By integrating these systems, data can be seamlessly synchronized, ensuring the digital twin always reflects the latest design changes.
  2. Interoperability: Omniverse has a strong focus on interoperability and supports a wide range of industry-standard formats and tools, including Autodesk software. This makes it easier to integrate with existing workflows, reducing friction and increasing efficiency.
  3. Real-Time Collaboration: By integrating with Autodesk and other design tools, Omniverse enables real-time collaboration. Designers and engineers can work on the same model simultaneously, with changes reflected instantly across all instances of the digital twin.
  4. Back-office Integration: By integrating digital twins with ERP and CRM systems, companies can feed operational data from the digital twin into these systems to enhance business processes. For example, data on machine performance and usage from the digital twin could be used to inform maintenance schedules, manage inventory, or assist with customer service.
  5. Comprehensive View: Integrating digital twins with back-office systems can help create a ‘single source of truth’, providing a comprehensive, real-time view of both operational and business data. This can enhance decision-making and enable more proactive and data-driven strategies.
  6. Automated Workflows: Integration with other systems can also help automate various workflows. For instance, if a digital twin detects an issue with a piece of machinery, it could automatically generate a maintenance request in the ERP system.
  7. Increased ROI: The integration of these systems increases the return on investment (ROI) by enhancing the utility of the digital twin, Autodesk tools, and back-office systems. It allows these different technologies to work together to optimize business processes.

Remember, successful integration often requires careful planning and execution, taking into consideration data compatibility, security, and compliance issues. But when done correctly, it can significantly enhance the value and utility of your digital twins and existing systems.

 

Keeping cost under control

Implementing digital twin technology can entail significant investment, but there are ways to effectively manage and control these costs. Here are a few key cost factors associated with digital twins and strategies for keeping them under control:

  1. Development Costs: The initial creation of a digital twin can be a considerable expense, as it involves mapping out the physical system, developing the digital model, and setting up the data collection and analysis framework. To control these costs, it’s essential to clearly define the scope and purpose of the digital twin at the outset. Focusing on specific, high-value use cases can help prioritize investments and ensure a return on investment.
  2. Software Costs: This includes the costs of the digital twin platform itself, as well as any additional tools or services required. Working with Nebul making use of the Nvidia Omniverse platform can help control these costs, as it offers a complete solution that integrates with various other tools, reducing the need for additional software investments.
  3. Data Management Costs: Digital twins generate vast amounts of data that need to be stored, managed, and analyzed. Implementing efficient data management strategies and using scalable storage solutions can help keep these costs under control.
  4. Hardware and Infrastructure Costs: Depending on the complexity of the digital twin, significant computational resources may be required. Leveraging cloud-based solutions can help manage these costs by providing scalable resources that can be adjusted as needs change, preventing unnecessary spending on over-provisioning.
  5. Maintenance and Updates: Like any technology, digital twins require ongoing maintenance and updates to remain accurate and effective. Planning for these costs as part of the initial budget and developing efficient processes for updates can help prevent unexpected expenses later on.
  6. Training Costs: Your team will need to be trained to use and maintain the digital twin, which should lead to increased efficiency and productivity.

By considering these factors and planning carefully, we help you effectively manage the costs associated with implementing and maintaining digital twin technology. It’s essential to remember that while there are upfront costs associated with digital twins, they have the potential to provide significant value and savings over the long term by improving efficiency, reducing downtime, and enabling more informed decision-making.

 

Showcases

BMW Group Celebrates Opening the World's First Virtual Factory.

Automaker brings power of industrial AI to its entire production network as part of its digital transformation.

Watch Video

Connecting NVIDIA OVX to Microsoft Teams

This demo showcases how real-time 3D collaboration can shorten the time between decision-making, action and feedback.

Watch Video

Benefits

Accelerated Today, Ready for Tomorrow

Enterprise HPC adjusted to your special needs

Less Wait

Spend less time waiting for processes to finish, and more time iterating and testing solutions with superior processing power.

Better Results

Analyze multi-terabyte datasets with high performance processing to drive higher accuracy results and quicker reporting.

Easy Scale

Accelerate and scale your data science toolchain with no need to learn new tools and minimal code changes.

Talk to an Expert?

Let’s discuss how we can help you

This field is for validation purposes and should be left unchanged.

Signup for our newsletter to stay informed on the latest