A digital twin is a living digital replica of a physical asset, process or system — not just a static model, but a model continuously updated with real-world data via sensors. It allows scenarios to be simulated, failures to be predicted, operation to be optimised, and changes to be tested without touching the physical system.
In an industrial environment, digital twins start simple — a machine model that consumes OEE data in real time and helps identify degradation patterns. They evolve into complete representations of production lines, where a change of sequence can be simulated before it is implemented. At the limit, whole-factory digital twins allow complex restructurings with much-reduced risk.
INFOS implements digital twins focused on clear operational value, not marketing exercises. A production line with a persistent bottleneck may benefit from a digital twin to test reorganisations before implementing them; a sensitive chemical process may benefit from a digital twin to simulate parameters outside the known window without risking real batches. The technical foundation combines data from KORA Productivity, IIoT, and simulation tools.