Digital twins in manufacturing: predictive maintenance that pays

How it works

• Sensors report vibration, temperature, current and other signals.
• The data flows to a model of the asset.
• The model compares current behaviour with normal and with known failure patterns.
• Maintenance is triggered by condition, not only by the calendar.

What makes it pay

• Pick assets where failure is costly and gives warning.
• Start with a clear failure mode and enough history to learn from.
• Connect predictions to a maintenance process that acts on them.

Where it goes wrong

• Not enough failure examples to learn from.
• Alerts that nobody trusts because of false alarms.
• A model with no owner, drifting as equipment and conditions change.

IICTP is a new independent credential and is not ISO/IEC 17024 accredited.