🧩 A digital twin is more than a 3D model.

It is a digital representation of a real-world asset that receives data about the asset’s condition and helps analyze what is happening now and what may happen next.

⚡ In the energy sector, digital twins are used to monitor equipment, diagnose faults, make forecasts, and support decision-making.

🤖 These systems are particularly valuable when sensor data, analytical algorithms, and machine learning are added to the physical model. The digital twin then becomes more than a copy of the asset: it becomes a tool for detecting deviations and forecasting changes in equipment condition. Put simply, while the real asset operates, its digital counterpart helps us understand how it is performing and what may happen next.