Predictive Maintenance
Stop Failures Before They Stop You
Our Predictive Maintenance dashboard continuously monitors machine health, detects anomalies, and recommends proactive interventions — so you avoid costly downtime and extend asset life.
The Challenge
“Downtime is the hidden factory tax.”
- Every unplanned stoppage disrupts production targets.
- Reactive maintenance = expensive emergency repairs + lost hours.
- Preventive schedules often waste resources by fixing machines too early.
The Solution
“Data-driven maintenance at the right time.”
- IoT sensors track vibration, temperature, pressure, and cycles.
- Machine learning models predict when failures are likely.
- Work orders are triggered only when needed, not on guesswork.
Key Capabilities
- Live temperature, vibration, current
- Oil & wear indicators by asset
- Fleet health overview
- Pattern-based alerts before failure
- Threshold & model-driven rules
- Noise filtering to reduce false alarms
- RUL projections & windows
- Usage/condition-based triggers
- Auto-recommended service slots
- Severity/probability ranking
- Spare parts & lead-time checks
- Impact on throughput & quality
- CMMS/ERP ticket creation
- Owner, SLA, and status tracking
- Close-the-loop verification
Dashboard Preview
Live condition data across assets with clear gauges for vibration, temperature, and current. Spot drift early.
- Condition triggers
- Fleet health
- Early drift detection
Algorithms surface abnormal patterns long before breakdowns. Review context and confirm actions with one click.
- Model + threshold rules
- Low alert fatigue
- Operator context
Plan service in optimal windows with Remaining Useful Life forecasts and automatic CMMS work orders.
- RUL-based windows
- Auto WOs
- Spares coverage
Business Impact
“From firefighting to foresight.”
Predict failures before they disrupt production.
Reduce emergency repairs and over-maintenance.
Service on condition, not on the calendar.
Keep lines running smoothly and predictably.