An operational digital twin (ODT) is a dynamic virtual replica of a real-life asset for owner operators. Integrate all industrial data, connect to physics simulators, deploy physics guided machine learning, and deliver intuitive data visualizations that drive agility and value.
Using Cognite Data Fusion (CDF), heavy-asset organizations are improving brownfield asset performance using digitally enhanced twins of equipment, assets, and asset fleets.
By integrating live operational data from sensor networks with historical data, operational digital twin delivers both real-time as well as complete historical data in one accessible HMI and API, enabling:
Cognite Data Fusion integrates all industrial data, including time series, process diagrams, 3D models, event histories, asset models, unstructured documents and more, making it available and actionable to all data consumers, human and machine, within and outside of the industrial enterprise.
Generate advanced models combining physics to generate synthetic data, complemented with ML/DL for scale. Observe, analyze, and optimize to deliver reliable forecasts and actionable insights.
Predict emerging maintenance issues before they become problems by combining historical data and real-time monitoring. Schedule and address concerns in a timely fashion, reducing costly disruptions and downtime.
Create a model for one asset, then scale it across an entire installation. Spend less time, effort, and resources on finding, cleaning, and contextualizing data, and more time on generating value.
Cognite Data Fusion combines data analytics with physics-based models to create a virtual clone of a physical asset. Run advanced simulations on the digital twin to test, observe, and predict outcomes, then implement them on physical systems.
Discover, test, and implement production optimization strategies and develop faster responses to adverse events. All thanks to an operational digital twin (ODT) informed by integrated data systems and providing advanced insights.