Operational Digital Twin

Build dynamic virtual models of physical assets, delivering real-time insights, accurate forecasts, and intelligent decision-making.

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Route to digital twin success

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More than just a digital twin project

We see digital twins as an enabling technology for business outcomes, leading to revenue growth, costs optimization and/or risk mitigation.

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Use relevant data only

We build the digital twin model using data that is relevant to the narrowly scoped use case. We begin working with the minimum necessary viable set of data.

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Keep it simple

We create simple "quick win" digital twin designs, focusing on ROI/KPIs. We demo them, collect feedback and use that to incrementally enhance the designs.

Driven by data. Optimized with Hybrid AI.

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:

  • Data that can be shared and acted on
  • Advanced, easy-to-access insights for all data consumers
  • Predictive maintenance
  • Production optimization
  • Improved safety
  • Faster responses to adverse events
Driven by Data

Actionable industrial data

Shaped by contextualization

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.

Hyper-advanced insights

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.

Predictive maintenance

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.

Scalable for operational excellence

From one to many
From one to many

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.

Physical to digital and back again
Physical to digital and back again

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.

Data to operational excellence
Data to operational excellence

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.


Discover how Yokogawa used a digital twin to contexualize data

Request a demo to start building your digital twin

Use cases

05th July 2021
How Energima built Properate on top of Cognite Data Fusion™
25th June 2021
How PGS optimized the speed of seismic surveying vessels
12th April 2021
How Cognite Remote powers OMV’s asset integrity operations framework

Operational Digital Twin: How Data Contextualization Provides A Complete, Actionable Understanding Of Industrial Operations