Private AI for manufacturing scientists.

Catch a developing fault before it becomes a stoppage

Compare each asset with its own operating baseline, detect drift and relate quality defects to process conditions.

Inputs: Time-stamped vibration, temperature and current readings; inspection images; operating loads; maintenance and production histories.

From observation to completed task

Raise a maintenance work order with the evidence, suggest an inspection window and route suspect products for review.

Draft a review agenda from approved production-science records

The supporting records include authorised test summaries, deviations and quality documents.

Scientists validate findings and release implications.

The systems involved

Sensor or historian feeds, inspection cameras, asset identifiers and a maintenance-system connector; predictive models need suitable history.

SOS AI configures the local models and tool permissions for this workflow. Actions in business software follow the authority you approve; uncertain cases and actions outside those limits go to the responsible person.

What a useful result must get right

Measure useful warning time, missed faults and nuisance alerts; independent safety controls remain authoritative.