Predictive Maintenance

Predictive Equipment Health Monitoring

The Problem

Traditional maintenance approaches are reactive and costly:

  • Unexpected breakdowns cause unplanned downtime and lost revenue
  • Over-maintenance wastes time servicing equipment that doesn't need it
  • No early warning of developing issues before they become critical
  • Manual inspections miss subtle degradation patterns
  • Poor maintenance records make it hard to predict failure patterns

Every hour of unplanned downtime costs money. Without sensor-based monitoring, you're always one step behind equipment failures.

The IoTReady Solution

Continuous equipment monitoring with predictive alerts—catch issues before they cause downtime

Vibration Monitoring

Detect abnormal vibration patterns that indicate bearing wear, misalignment, or imbalance. Get alerts before failure.

Temperature Tracking

Monitor equipment temperature continuously. Identify overheating motors, bearings, or electrical components early.

Predictive Alerts

Machine learning identifies patterns that precede failure. Schedule maintenance during planned downtime.

Maintenance History

Complete audit trail of all maintenance activities, parts replaced, and sensor readings for root cause analysis.

Asset Tagging

Track maintenance schedules, spare parts inventory, and service history for every piece of equipment.

Integration Ready

Push maintenance work orders directly to CMMS or ERP systems when alerts are triggered.

Technology Stack

We deploy the right sensors based on equipment type and failure modes

Vibration Sensors

Best for: Rotating equipment (motors, pumps, fans, compressors)

Wireless vibration sensors detect changes in amplitude and frequency. Alert on bearing wear, imbalance, misalignment.

Use cases: Manufacturing machinery, HVAC systems, industrial motors

Temperature Sensors

Best for: Electrical panels, motors, bearings, ovens

Monitor temperature continuously. Alert when temperatures exceed normal operating ranges or show unusual trends.

Use cases: Electrical equipment, furnaces, cold chain, process heating

Current Sensors

Best for: Electric motors and pumps

Monitor power consumption patterns. Detect motor degradation, mechanical binding, or efficiency loss.

Use cases: Motor health monitoring, energy management

Asset Tags (RFID/QR)

Best for: Maintenance tracking and history

Link sensor data to specific equipment. Track maintenance schedules, spare parts, and service records.

Use cases: Equipment registers, CMMS integration, compliance

Real-World Results

Flipkart Cold Chain

Refrigeration Monitoring

Temperature monitoring for cold storage units. Alerts prevent spoilage and ensure compliance with cold chain requirements.

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How It Works

1. Sensor Installation

Install wireless sensors on critical equipment. Configure baseline readings for normal operation.

2. Continuous Monitoring

Sensors collect vibration, temperature, and power consumption data continuously. Data streams to cloud platform.

3. Anomaly Detection

Machine learning algorithms identify patterns that deviate from normal operation. Prioritize alerts by severity.

4. Alert & Work Order

Maintenance team receives alert with equipment ID, location, and sensor readings. Work order created automatically.

5. Feedback & Learning

Record maintenance actions and outcomes. System learns to predict failures more accurately over time.

From Reactive to Predictive

❌ Reactive Maintenance

Fix equipment after it breaks

High downtime, expensive repairs, lost production

⚠️ Preventive Maintenance

Service on fixed schedules

Over-maintenance, still miss unexpected failures

✅ Predictive Maintenance

Service based on actual condition

Minimize downtime, optimize maintenance spend

Business Impact

30-40%

Reduction in Downtime

Catch issues before they cause failures

25%

Lower Maintenance Costs

Eliminate unnecessary servicing

15-20%

Improved OEE

Overall Equipment Effectiveness

3-5x

Equipment Lifespan

Extend asset life with proactive care

Frequently Asked Questions

How long does it take to deploy predictive maintenance? ▼
Typically 2-4 weeks for initial deployment. We start with pilot equipment (install sensors, configure baselines, set alert thresholds) in week 1, monitor for 1-2 weeks to establish normal patterns, then expand to additional equipment. Most customers see their first predictive alerts within 2-3 weeks.
What types of equipment can you monitor? ▼
We monitor rotating equipment (motors, pumps, fans, compressors) with vibration sensors, electrical equipment (panels, motors) with temperature and current sensors, HVAC systems with temp/vibration monitoring, and industrial ovens/furnaces with temperature tracking. Any equipment with measurable failure indicators can be monitored.
Does this integrate with our CMMS or ERP? ▼
Yes. We integrate with SAP, Oracle, IBM Maximo, and custom CMMS systems via APIs. When sensors detect anomalies, the system can automatically create work orders in your CMMS, trigger maintenance workflows, and log all sensor data for equipment history. See our ERP integration pages for technical details.
How accurate are the predictive alerts? ▼
Accuracy improves over time as the ML models learn your equipment patterns. Initially, expect 70-80% accuracy with some false positives. After 3-6 months of learning, accuracy reaches 90-95%. Our approach: prioritize alerts by severity, allow feedback on false positives, and continuously refine thresholds based on actual failure data.
What's the typical ROI for predictive maintenance? ▼
Most customers see 30-40% reduction in unplanned downtime and 25% lower maintenance costs by eliminating unnecessary servicing. Equipment lifespan extends 3-5x with proactive care. 15-20% improvement in Overall Equipment Effectiveness (OEE). ROI typically realized within 6-12 months depending on equipment value and downtime costs.
Do we need to replace existing equipment? ▼
No. Wireless sensors install non-invasively on existing equipment—magnetically mounted vibration sensors, clamp-on current sensors, surface-mount temperature sensors. No equipment modifications required. Works with any motor, pump, or compressor regardless of age or brand.
What if our equipment is in harsh environments? ▼
Our sensors are industrial-grade with IP65+ ratings—designed for dust, moisture, temperature extremes, and vibration. Deployed successfully in steel mills, cement plants, mining operations, and outdoor installations. Battery-powered sensors eliminate wiring in hazardous areas.
Can we track maintenance history and spare parts? ▼
Yes. Link sensor data to specific equipment via asset tags (RFID/QR). Track complete maintenance history, spare parts consumed, service providers, and failure patterns. When an alert triggers, technicians see full equipment history instantly. All records integrate with your CMMS for centralized asset management.
How is this different from preventive maintenance? ▼
Preventive maintenance services equipment on fixed schedules (every 30 days, 1000 hours) regardless of actual condition—leads to over-maintenance and still misses unexpected failures. Predictive maintenance services based on actual equipment condition from sensor data—only when needed, before failures occur. Result: lower costs, less downtime, longer equipment life.
What about data security? ▼
We support on-premise deployments for sensitive facilities, encryption at rest and in transit, role-based access controls, and private cloud hosting. Sensor data stays within your network if required. Complete audit trails for all alerts, maintenance actions, and system changes.

Ready to Predict Equipment Failures?

Reduce downtime and optimize maintenance costs with sensor-based condition monitoring

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