WHAT IS DIGITAL TWIN
A Digital Twin (DT) is a virtual representation of a physical object, system, or process. It’s created using data from the real-world counterpart and allows for detailed monitoring, analysis, and simulation.
Digital twins are often used in various industries, including manufacturing, healthcare, and IoT (Internet of Things) applications. They enable organizations to gain insights, optimize performance, and make data-driven decisions by replicating physical objects or systems in a virtual environment. The DT technology can help improve efficiency, reduce downtime, and enhance overall productivity by providing a dynamic and interactive model of the real-world entity it represents.
Why Digital Twin?
Digital twin technology is revolutionizing the way businesses operate, offering a range of benefits that can help improve efficiency, reduce risk, and increase agility.
One of the key advantages of digital twin technology is its ability to perform predictive maintenance. By monitoring the performance of physical assets in real-time, businesses can identify when maintenance is required and take action before a failure occurs. This not only reduces downtime but also extends the lifespan of equipment, improving its overall performance.
Another major benefit of digital twin technology is its ability to simulate different scenarios and optimize processes. For example, businesses can use a digital twin to test new products or materials, simulate changes to production lines, or even optimize their supply chain.
It can also improve collaboration across departments and stakeholders. By providing real-time data and insights on the performance of physical assets, multiple stakeholders can work together to improve communication and ensure everyone is working towards the same goals.
DIGITAL TWIN AS A SOLUTION
We offer a Digital Twin Infrastructure (DTI) that revolutionizes how businesses connect, manage, and leverage their digital assets. Our DTI solution provides standardized data integration, robust security, powerful insights and much more.
- No additional tools for customers needed to access information
- Enabling automatic use of data by machine accessible interfaces
- Enable customers to retrieve a copy of the data in standardized form (AASX-file)
- Secure, shielded and authored access to information without direct access to internal systems
- Authentication of users (allows to share some information only to paying customers)
- Running business applications on top of the available data
- Connecting to multiple internal systems by using easy to manage rule sets and automated suggestions system. Integrates to GraphDB and PLM with ease.
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Allows for the dynamic creation and provisioning of digital twins for various physical assets and systems.
Highly scalable, accommodating the addition of more assets and data sources without significant constraints.
Incorporates robust security measures to protect sensitive data and prevent unauthorized access.
Facilitates effortless updates and modifications to digital twins and their associated data models.
Uses semantic data modeling to provide context and meaning to data points.
Offers diverse output formats for presenting and sharing digital twin data.
THE NEOCEPTION® DIGITAL TWIN INFRASTRUCTURE
Dive into the key layers of our solution, each playing a distinct role in enhancing data exchange and digital twin capabilities.
ECLASS is the globally recognized ISO/IEC-compliant industry standard, serving as the reference data standard for classifying and describing products and services. More than 4,000 customers are already successfully using the 45,000 classes and 19,000 properties in 16 languages from ECLASS for digital data exchange.
Our partner provides standardized frameworks that provide unique identifiers for semantic data points, enabling clear communication and data consistency across systems.
The Industrial Digital Twin Association is the one-stop shop for the Digital Twin – an alliance of active creators working together to standardize the Industrial Digital Twin.
The association standardizes templates for various data models, such as digital nameplates, ensuring uniformity across products in the DT.
- Digital Twin (DT):
A digital replica of a physical asset, process, or system that simulates its behavior, characteristics, and data in real-time or historically. It provides insights, analysis, and testing capabilities.
- API (Application Programming Interface):
A set of rules and protocols that allows different software applications to communicate and interact with each other, enabling automated data exchange.
- Distributed Data Spaces:
Collaborative environments or platforms (e.g., Manufacturing-X, Gaia-X, Catena-X) that enable organizations to share and access data across a network of participants.
A database management system that uses graph structures to store and query data, useful for representing complex relationships within the DTI.
- PLM (Product Lifecycle Management):
Software and systems used to manage the entire lifecycle of a product, from design and development to manufacturing and maintenance.
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