What is a digital twin?
Short answer
A digital twin is a virtual replica of an asset, system, or process, fed in real time by IoT data, that lets you simulate, predict, and optimize. From a wind turbine to a distribution network, a twin connects physical model, telemetry, and analytics to support evidence-based decisions.
Three useful types
Asset twin (one machine): ideal for predictive maintenance. System twin (one plant): operations optimization. Process twin (logistics chain): scenario simulation. Cost and benefit grow with scope.
From telemetry to model
A useful twin needs reliable telemetry (IoT sensors over IoT SIM or LoRa), a platform that syncs real data with a physical model (fluid, thermal, mechanical), and a UI that lets users 'play' with the twin. Without the three, it's a dashboard with a fancy name.
How to start pragmatically
Pick a critical asset, instrument 3-5 signals that matter, build the reduced twin (don't model everything), measure results, scale. Plant-wide twins without a prior pilot rarely end well.
- Asset twin: maintenance
- System twin: operations
- Process twin: simulation
- Instrument 3-5 key signals
- Pilot before big bang
2-week digital twin validation
We help you pick the asset, sensors, and metrics: a 2-week validation with measurable output before investing.
Frequently asked questions
Common tools?+
Azure Digital Twins, AWS IoT TwinMaker, Siemens MindSphere, Bentley iTwin, PTC ThingWorx, and open frameworks (Eclipse Ditto). Choose by sector and OT stack more than by hype.
How much does a digital twin cost?+
Simple asset twin: €20-80k in year one. Plant twin: €150-500k+ with 24-36 month payback. Without a measurable pilot, any figure is fiction.
Is AI required?+
No. Many useful twins rely on physical models and rules, no ML. Add ML when you have enough data and a problem where analytical models fall short.
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