Predictive Maintenance AI
Unplanned machine downtime is the single largest drain on factory profitability for Indian manufacturing plants. When an induction motor, CNC spindle, compressor, or rolling mill bearing fails unexpectedly, the entire line halts for days while replacement parts are sourced. Our Predictive Maintenance AI platform monitors continuous vibration and thermal telemetry to predict mechanical degradation 14 to 30 days before failure.
Technical Anomaly Detection Workflow
High-Frequency FFT Vibration Analysis
Captures tri-axial acceleration up to 10 kHz. Calculates Fast Fourier Transforms (FFT) to distinguish inner race, outer race, ball, and cage bearing fault frequencies.
Machine Learning Degradation Curves
Supervised and auto-encoder anomaly models benchmark nominal operating baselines against ISO 10816 standards, continuously projecting Remaining Useful Life (RUL).
Thermal Drift & Current Signature (MCSA)
Correlates motor surface temperature and split-core current harmonic distortion to detect phase imbalance, winding overheating, and mechanical binding.
Multi-Tier Early Warning System
Automated priority alerts dispatched via SMS, WhatsApp, and factory floor sirens when vibration velocity breaches critical thresholds (e.g. > 4.5 mm/s RMS).