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AI PREDICTIVE MAINTENANCE

Know which asset will fail — before it does

PlantOps360 turns sensor, IIoT, and maintenance-history data into early failure warnings, so you fix problems on your schedule instead of reacting to breakdowns. Less downtime, lower cost, and safer plants.

−45%unplanned breakdowns
−30%maintenance cost
3–6wksearlier failure warning
Predictive Maintenance
PlantOps360 module
Live
Assets monitoredReal-time
Early warnings2 this week
Fleet health96%
Auto work ordersOn trigger
WHY IT MATTERS

Stop paying the price of surprise failures

Every unplanned breakdown costs production, spares, overtime, and safety risk. Predictive maintenance gives you the lead time to act before failure — turning emergencies into planned work.

−45%

Fewer breakdowns

Catch degradation early and intervene before assets fail in production.

−30%

Lower maintenance cost

Do work only when the asset needs it — no over-servicing, no emergency repairs.

+20%

Longer asset life

Address root causes early to extend the usable life of critical equipment.

+15%

Higher availability

Plan interventions during windows that protect throughput and OEE.

Safer operations

Prevent catastrophic failures that put people and the environment at risk.

−25%

Leaner spares

Order parts just in time with confident lead-time from early warnings.

CAPABILITIES

From raw signals to the right work order

A complete predictive workflow that connects your equipment data to action in PlantOps360 — no data-science team required.

IIoT & sensor integration

Connect vibration, temperature, pressure, current, and more from your assets and gateways.

AI failure prediction

Machine-learning models flag anomalies and estimate remaining useful life.

Live asset health scoring

Every critical asset gets a real-time condition score with drift and threshold alerts.

Smart alerts & routing

Warnings reach the right team by criticality, before failure — not after.

Auto-triggered work orders

Predictions raise a corrective or PM work order automatically with context attached.

Trends & RUL analytics

Visualize degradation trends and prioritize by risk across the fleet.

HOW IT WORKS

How predictive maintenance works in four steps

1

Connect

Stream sensor and IIoT data into PlantOps360 alongside maintenance history.

2

Detect

AI models learn normal behavior and flag anomalies and early degradation.

3

Predict

Get remaining-useful-life estimates and a prioritized, risk-ranked queue.

4

Act

A work order is auto-generated and assigned so the fix happens on your schedule.

WHO IT'S FOR

Built for asset-intensive plants where downtime is expensive

Predictive maintenance delivers the biggest returns on critical rotating and process equipment across heavy industry.

Rotating equipmentProcess plantsPower & utilitiesChemicalsCement & steelFood & beverage
WHY PREDICTIVE WINS

Stop over-maintaining. Stop reacting.

Most plants swing between fixing things too late and servicing things too often. Predictive maintenance ends both — you act exactly when the asset needs it.

Reactive
Run to failure

Fix it after it breaks.

Unplanned downtime & lost production
Emergency repairs and overtime
Collateral damage to other parts
Safety and compliance risk
Preventive
Fixed calendar

Service on a fixed schedule.

Over-maintenance of healthy assets
Wasted parts and labor
Still misses random failures
Better — but not optimal
PLANTOPS360
Predictive
Condition-based

Act only when data says so.

Fix only what actually needs it
Weeks of early warning
Maximum uptime and asset life
Lowest total cost of ownership
WHAT WE CATCH

Detect the failures that stop production

PlantOps360 learns each asset's normal behavior and flags the developing faults that lead to unplanned downtime — long before they become failures.

Bearing wear & spallingShaft misalignmentRotor imbalanceLubrication breakdownCavitation & flow faultsMotor winding faultsOverheating & thermal driftBelt & coupling wear

Parameters monitored

From sensors and IIoT gateways you already have.

Vibration
Temperature
Pressure
Current & voltage
RPM / speed
Oil quality
Acoustic
Flow
PROVEN IMPACT

The numbers reliability teams care about

−43%
unplanned downtime
−36%
spare-parts inventory cost
−25%
maintenance response time

“PlantOps360 flagged a bearing fault three weeks before it would have failed. We planned the fix into a weekend shutdown instead of losing a full production day.”

Reliability Manager · Process Manufacturing

Frequently asked questions

Predictive maintenance uses live sensor, IIoT, and maintenance-history data to detect early signs of degradation and predict when an asset is likely to fail — so you can act before it does.
Not necessarily. PlantOps360 works with sensors and IIoT gateways you already have, and can scale up as you add condition monitoring to more critical assets.
No. The AI models, health scoring, and alerting are built in. Warnings arrive as clear, prioritized work — not raw data you have to interpret.
When a prediction crosses a threshold, PlantOps360 can automatically raise a corrective or preventive work order with the asset context attached.
Critical rotating and process equipment — pumps, motors, compressors, fans, and reactors — where unplanned failure is expensive or unsafe.
Plants typically see up to 45% fewer unplanned breakdowns and around 30% lower maintenance cost as they shift from reactive to predictive work.

See what your plant data is trying to tell you

Book a demo and we'll show how PlantOps360 predicts failures on your critical assets.

PlantOps360

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