Digital Twins in Manufacturing: Model, Measure, Update
Define what a useful digital twin is and how it differs from a static simulation or dashboard.
The essential loop
A digital twin links a physical asset with a model and recurring data exchange. The model is updated as the asset changes.
Levels of fidelity
A twin may represent geometry, process state, degradation or production flow. Fidelity should match the decision being supported.
Data and observability
Sensors must capture variables that make hidden states identifiable. More data does not compensate for poor measurement design.
Validation and governance
Models drift as equipment, materials and operating practices change. Versioning, uncertainty and ownership are required.
Engineering takeaway
Begin with a specific decision—quality prediction, maintenance or optimisation—and build only the model and data loop needed for it.