What is Digital Twin?

Turbines, buildings, supply chains and production lines are expensive to experiment on. With a digital twin, engineers can try a “what if” on the model first and find problems before they happen on site.

Built on a knowledge graph and a shared ontology, a twin can combine sensor readings, maintenance logs, design specifications and environmental data in one model. That is the difference between a 3D picture of an asset and a twin that can answer questions spanning engineering, operations and maintenance.

Energy companies use twins for asset integrity, manufacturers for predictive maintenance, cities for managing infrastructure and hospitals for monitoring patients.

Most digital twin architectures have three layers:

1. Data ingestion. Sensors, SCADA systems, IoT platforms and business systems feed live and historical data into the twin.

2. Semantic model. An ontology describes the kinds of asset, their properties and how they connect. This is what gives a raw reading its meaning: a temperature belongs to a particular valve, on a particular pipeline, in a particular facility.

3. Analytics and simulation. With the data in context, teams can run physics simulations, machine learning models and rule-based alerts. The knowledge graph also answers questions across domains, such as “which assets in Region X are overdue for maintenance and running above their temperature limit?”

Offshore wind. An operator can build a twin of each turbine that links structural models, wind and wave data and maintenance records. Analytics on the twin can pick up early signs of bearing wear, so the repair is planned instead of forced by a breakdown.

Smart buildings. A property manager can twin a whole campus, combining building management data, occupancy sensors and energy meters, and use it to adjust heating and cooling schedules to how the buildings are actually used.

Pharmaceutical manufacturing. A twin of a production line can link batch records, equipment sensors and quality control results, so deviations show up while the batch is running and release takes less time.