Platform Features · Predictive Maintenance
Hear the failure coming — 48 to 96 hours early.
ML models score every machine's health 0–100 daily from vibration, current and thermal trends. Degradation triggers a recommendation with estimated time-to-fault and the parts to pre-order.
Daily health scores 0–100Time-to-fault estimatesParts recommendationsTrend explanationsFleet rankingWhatsApp escalation
The problem it kills
Every unplanned breakdown was once a prediction nobody made.
SUDDEN
“It just failed”
Machines rarely just fail — they announce it in signatures for days. Nobody was listening. Now something always is.
CALENDAR
Time-based guessing
Calendar PMs service healthy machines and miss dying ones. Condition-based scheduling puts effort where the risk is.
SPARES
The part that isn't there
The breakdown is 4 hours; waiting for the bearing is 4 days. Time-to-fault estimates buy you the procurement window.
How it works
Predictive Maintenance, the MachineWise way.
Deployed software-first in under an hour, included in one subscription — no per-module licensing.
SCORE
Health 0–100, daily
- Fused vibration, current and thermal features
- Machine-type-specific models
- Fleet-wide ranking: worst machines first
- Score history shows degradation arcs
PREDICT
Time-to-fault, estimated
- Trending machines flagged with ETA to failure
- Likely component identified where signatures allow
- Confidence indicated honestly — no fake certainty
- 48–96h typical early-warning window
ACT
From warning to work order
- One tap: prediction → maintenance ticket
- Recommended parts listed for pre-order
- Intervention windows suggested around production
- Outcome logged to improve the model
48–96hTypical early-warning lead time
60–80%Reduction in unplanned breakdowns
3–5×ROI vs reactive maintenance
Keep exploring
Goes deeper with the rest of the platform.
Ready when you are
See Predictive Maintenance running on machines like yours.
A 30-minute walkthrough on a live dashboard seeded with your machine types. No obligation.
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