Equipment & Assets
A deep asset model with criticality, warranty, manufacturer, condition and full maintenance history per item. Every event that touches the asset is logged, making it the highest-signal source for predictive maintenance models.
Functional areas this module covers.
Asset registry
Hierarchical equipment with parent-child relationships, location and ownership.
Condition surveys
Periodic surveys with scoring against standardised criteria.
Maintenance history
Every task, part, technician and outcome that touched the asset.
Warranty & lifecycle
Install/commission dates, warranty windows, expected and projected end of life.
1 core table documented in detail.
Unlocked by the depth of this module's schema.
Predictive failure
Model failure probability per asset class using meter, log and event data.
Replace vs. repair
Score each asset on remaining useful life vs. cost-to-keep.
Criticality-aware prioritisation
Weight maintenance backlog by asset criticality, not raw count.
Sample queries an AI agent can resolve against this module.
“List equipment with three or more corrective tasks in the last 90 days.”
“Which critical assets are within six months of warranty expiry?”
“Show MTBF trend for chillers across the portfolio.”
Pre-built summary views and the metrics teams track.
Summary views
- Monthlymonthly_equipment_summaryFailures, downtime and cost per equipment class.
- Quarterlyquarterly_equipment_condition_summaryCondition score distribution.
Key KPIs
- MTBFMean time between failures per asset class.
- Downtime hoursTotal unavailable hours per critical asset.
- Warranty leakageCost of work done on assets still under warranty.
Where this module connects across the platform.