Real-Time Digital Twin Synchronisation Methods
topic
Digital twin synchronisation maintains correspondence between virtual and physical machine states by continuously updating simulation model states with real machine sensor measurements using Kalman filtering, data assimilation, or state estimation algorithms that reconcile model predictions with measured values, correcting for model inaccuracies and unmeasured disturbances to maintain a virtual machine state estimate that accurately reflects the current condition of the physical machine.
Role
Ensures that digital twin predictions remain accurate representations of physical machine behaviour over time by continuously correcting the simulation state from sensor measurements, with synchronisation quality being the critical technical requirement that determines whether the digital twin provides reliable guidance for production decisions or gradually diverges from physical reality through accumulated model errors that would make twin-based predictions unreliable.