+91-9908230104info@suryaelectronics.inHyderabad, Telangana, India
๐Ÿ”ง AI ยท Condition Monitoring ยท Reliability

Predictive Maintenance

AI-powered condition monitoring and failure prediction systems that detect equipment degradation weeks before failure โ€” eliminating unplanned downtime and transforming maintenance from reactive to predictive.

40%
Downtime Reduction
6ร— ROI
Typical Return
Real-Time
Monitoring
Asset Classes
Covered: 50+

From Reactive to Predictive Operations

Surya's predictive maintenance platform combines edge IoT sensors, machine learning models and maintenance workflow integration to keep critical infrastructure running reliably.

Vibration and Temperature Sensors
Sensing
Condition Monitoring Sensors
Wireless IoT Sensor Network

Industrial-grade wireless vibration, temperature, current and acoustic emission sensors that attach to critical assets โ€” motors, pumps, gearboxes, fans and bearings โ€” streaming data continuously to the edge analytics layer without wiring modifications to existing equipment.

  • Wireless IIoT sensors โ€” zero wiring modification
  • Vibration, temperature, current and ultrasound
  • 5-year battery life on standard monitoring cycles
  • IP67 rated for industrial environments
  • Sub-second data sampling for fast-fault detection
AI Analytics Platform
AI ยท Analytics
Failure Prediction Engine
Machine Learning Fault Forecasting

ML models trained on asset-class-specific failure signatures โ€” bearing raceway defects, motor winding insulation degradation, gearbox tooth wear and pump cavitation โ€” issuing probability-ranked failure alerts with estimated remaining useful life calculations.

  • Asset-specific failure mode libraries
  • Remaining Useful Life (RUL) estimation
  • Failure probability ranking and trending
  • Automated work order creation in CMMS
  • Root cause guidance with recommended actions
Maintenance Dashboard
Dashboard
Maintenance Intelligence Dashboard
Fleet-Wide Asset Health Overview

Single-pane-of-glass dashboard providing real-time asset health status across the entire fleet or plant โ€” colour-coded by health score, with drill-down to individual sensor readings, trend charts, historical events and scheduled maintenance actions.

  • Fleet-wide asset health heatmap
  • Individual asset sensor trend charts
  • Maintenance history and action tracking
  • Mobile app for field technician access
  • Customisable KPI and reliability reporting
Railway Track Monitoring
Railway
Railway Asset Monitoring
Track, Rolling Stock & Infrastructure

Specialised predictive maintenance for railway assets โ€” monitoring loco traction motors, wheel bearing health, track geometry sensors and overhead equipment โ€” aligned with Indian Railways and metro maintenance workflows and RDSO inspection standards.

  • Rolling stock bearing and motor monitoring
  • Track geometry measurement integration
  • Overhead equipment health tracking
  • Alignment with IR maintenance schedules
  • RDSO-compatible reporting and documentation

Why Choose Surya Electronics

๐Ÿ“Š
Proven ROI Model
Customers typically realise 4โ€“6ร— ROI within 18 months through reduced emergency repairs, extended asset life and optimised maintenance scheduling.
๐Ÿ”ง
CMMS Integration
Two-way integration with popular CMMS platforms โ€” SAP PM, IBM Maximo and IndGIS โ€” means predicted faults automatically generate work orders in existing workflows.
โšก
Fast Deployment
Wireless sensors and cloud-optional architecture means first sensors are live and generating data within days of project kick-off โ€” not months.
๐ŸŒ
Cross-Sector Coverage
Platform supports railway, metro, airport, mining and industrial assets โ€” one tool for organisations operating across multiple sectors.
๐Ÿ”’
Data Security
All sensor data processed on-premise or in private cloud โ€” no raw operational data transmitted to third-party systems.
๐ŸŽ“
Technician Upskilling
Comprehensive training programme transforms maintenance teams from reactive fault-finders to proactive reliability engineers.

Eliminate Unplanned Downtime

Start your predictive maintenance journey โ€” discuss sensor deployment, ML model development or CMMS integration with our reliability engineering team.