Digital Twins for Asset Integrity

What this topic covers

How models, configuration and condition data can support scenario and lifecycle analysis.

Core ideas

A digital twin is useful only when its model and asset configuration remain aligned with reality.

Condition data can update assumptions or highlight divergence between predicted and observed behaviour.

High-fidelity models are not always necessary; the model should match the decision.

Program tradeoffs

Data must retain asset identity, timestamp, units and operating context to support reliable trend analysis.

What good evidence looks like

Anomalies and model predictions are decision support, not automatic proof of failure.

Lifecycle perspective

OT security should protect monitoring availability and integrity without interfering with safe operation.