Predictive Maintenance
Predictive maintenance workflows combine operating signals, equipment history, inspection evidence, and maintenance actions. FactVerse AI Agent helps teams interpret risk signals, prepare the next checks, and keep the final decision inside the customer's maintenance governance process.
Operating context
| Context | FactVerse source | Why it matters |
|---|---|---|
| Equipment identity | FactVerse Platform assets, models, location, ownership, and criticality | Keeps analysis attached to the right asset and operating responsibility |
| Signal history | DFS time series, events, alarms, and data quality checks | Separates useful trend changes from gaps, stale feeds, or integration noise |
| Maintenance record | Inspector work orders, inspections, operator notes, and completed actions | Links current risk to what has already been checked or repaired |
| Knowledge reference | Manuals, SOPs, failure modes, and approved troubleshooting material | Grounds suggested checks in controlled knowledge instead of free-form guesses |
Workflow
- Detect a signal change, anomaly, repeated alarm, or maintenance question.
- Attach asset metadata, recent inspections, operating conditions, and previous work orders.
- Compare the signal with known failure patterns, data quality status, and recent field evidence.
- Produce a risk explanation with source references, confidence notes, and missing checks.
- Prepare an Inspector work order draft or inspection checklist for human approval.
- Feed the completed action and operator feedback back into the predictive maintenance loop.
Typical outputs
- Risk explanations for pumps, fans, compressors, HVAC equipment, utilities, and production support assets.
- Suggested inspection steps that show why each check is needed.
- Work order drafts with asset context, symptom history, and supporting evidence.
- Data quality notes that highlight missing telemetry, stale values, or inconsistent source mappings.
- Maintenance learning records that connect completed work with later model and knowledge updates.
Governance
Predictive maintenance should be treated as decision support. FactVerse AI Agent can organize evidence and propose next checks, while maintenance owners approve work, schedule downtime, and decide whether a recommendation is operationally appropriate.