Digital Twin Basics

• reader: an engineer new to digital twins who will operate one, not build one
• scope: vocabulary, keeping a twin honest, and integration; deliberately no vendor tooling

Part I: What a Twin Is

Vocabulary and levels of integration

Establish the model/shadow/twin distinction as a property of data flow, and why holding it strictly keeps expectations honest.

The three levels

Model, shadow, twin -- each defined by its data flow.

What a twin is for

Monitoring, prediction, optimisation, record-keeping.

Part II: Keeping It Honest

Synchronisation and staleness

The twin must know its own age: synchronisation strategies, staleness budgets, and marked reads.

Synchronisation strategies

Pull, push and event-driven flows, and what each costs.

Marked reads

Staleness budgets from decision physics; every read carries its age.