Digital-Twin Operations
A digital twin is a running simulation kept synchronized with the real machine, used to see inside it, test decisions, and predict what happens next.
Definition
A digital twin is not a static 3D model; it is a live, physics-based model that ingests plant data and stays aligned with the current state of the hardware. Where sensors cannot reach, the twin estimates. Where operators must decide, the twin lets them try the decision in simulation first.
What it provides
- Visibility into states no sensor measures directly, such as internal current profiles.
- A safe sandbox to test control changes before applying them.
- Short-horizon prediction of where the plant is heading.
- A record that ties every action to the state it was taken in.
Keeping it synchronized
The twin is corrected continuously by comparing its predictions to measurements and updating its internal state, a process shared with state estimation and calibration. Fidelity is chosen per task: fast reduced models for control, high-fidelity models for analysis, discussed in fidelity levels.
For Kronos
The Hyperion, Aegis, and MetroVolt machines are design and simulation efforts today; construction begins Q2 2027. Building the twin now means the operational tool matures alongside the hardware, and the control policies are trained against the twin long before first plasma.
Beyond a single unit
Because each twin is a structured model, twins across a fleet can share what they learn, the basis of fleet learning. A correction discovered on one unit updates the priors for the next.
Discipline
A twin that drifts from reality is worse than none, so its agreement with data is monitored and reported, and every version is tracked for reproducibility.