Digital twins are useful when they improve real decisions on reliability, throughput, and maintenance timing. Start with one critical asset class, not the whole plant.
What an SME digital twin needs
- Reliable telemetry and event history.
- Asset context: configuration, maintenance logs, and known failure modes.
- Scenario logic for thresholds and intervention timing.
- A dashboard that supports daily decisions.
Start small, prove value
Pick one recurring failure pattern. Build a twin model around that pattern and measure whether intervention lead time improves.
Common pitfalls
- Building visual models without action workflows.
- Ignoring data quality and sensor placement.
- No ownership for review and model updates.
A digital twin should reduce uncertainty, not create another reporting layer that nobody uses.