Predict equipment failures before they shut down your line
AI that analyzes sensor data, operating logs, and maintenance history to predict failures days or weeks before they happen. Replace reactive maintenance with intelligent, data-driven decisions.
Unplanned downtime is costing your operation crores per year
Reactive maintenance means fixing equipment after it breaks. Scheduled maintenance means replacing parts on a fixed calendar, whether they need it or not. Both approaches are wasteful. Your equipment generates sensor data around the clock, but nobody is analyzing it for early warning signs of failure.
40%
Of unplanned downtime preventable with predictive maintenance
Crores
Lost per year to unplanned equipment downtime in Indian manufacturing
30%
Of scheduled maintenance is unnecessary (parts still healthy)
10x
Cost of unplanned repair vs planned repair
How Optivus builds predictive maintenance systems
We connect to your equipment sensor data, analyze patterns, and build ML models that predict failures before they happen. Your operations team gets actionable alerts: which machine, what type of failure, how urgent, and when to schedule maintenance.
Connect sensor data
Integrate with your existing SCADA systems, IoT sensors, PLCs, and historian databases. No new hardware required.
Train failure models
Build ML models on your historical failure data and sensor patterns. Identify the signatures that precede each failure type.
Deploy monitoring
Real-time monitoring with anomaly detection. Alerts when equipment deviates from normal operating patterns.
Optimize scheduling
Maintenance scheduling based on predicted remaining useful life, not fixed calendars. Maximize uptime, minimize cost.
Key capabilities
Sensor data analysis
Ingest and analyze data from vibration sensors, temperature probes, pressure gauges, current monitors, and any other sensor your equipment has.
Anomaly detection
Detect deviations from normal operating patterns that signal developing failures. Catch issues before they become visible.
Failure prediction
ML models trained on your failure history predict which equipment will fail, what type of failure, and how soon.
Remaining useful life estimation
Estimate how much useful life remains for critical components. Replace before failure, not on a fixed schedule.
SCADA/IoT integration
Connect to existing SCADA systems, PLCs, IoT platforms, and historian databases. Works with your current infrastructure.
Alerting and dashboards
Real-time dashboards showing equipment health. Configurable alerts to maintenance teams via email, SMS, or integrated systems.
Results you can expect
40%
Reduction in unplanned equipment downtime
30%
Reduction in unnecessary scheduled maintenance
Days/weeks
Advance warning before equipment failures
10x
Cost saving of planned vs emergency repairs
Our AI implementation process
Every engagement follows the same four-phase structure.
Scope
Map the workflow, define success criteria, lock deliverables.
Build
Weekly working demos. Direct channel with the build team.
Ship
Production deployment on your cloud with monitoring.
Scale
Optimize on real usage. Expand to adjacent workflows.
Frequently asked questions
Related solutions
For your industry
Ready to get started?
Book a 25-minute call. Bring your workflow and we will show you exactly how we would approach it.