AI and Machine Learning for industrial reliability

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AI and Machine Learning glossary

Model drift

Model drift occurs when the data, equipment, process, or relationship a model learned changes enough that performance may decline.

STAHDRIFTMONITOR THE MODEL
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Connected industrial monitoring system used to track data and model performance

Practical guidance

Model drift

Maintenance, sensor replacement, control changes, production changes, aging, and seasonal conditions can all shift the data seen by an industrial model.

Drift management requires performance checks, data-quality monitoring, review of human overrides, and a defined path to recalibrate, retrain, restrict, or retire the model.

Key points

  • Monitor inputs and outcomes
  • Record maintenance and configuration changes
  • Review overrides and false alerts
  • Define recalibration and retirement criteria
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