Failure Prediction
Advanced AI algorithms analyze sensor data to predict equipment failures up to 30 days in advance
AI Analysis Pipeline
Signal Processing
FFT & Wavelet Analysis
Transform raw sensor data into frequency domain for pattern detection
Feature Engineering
PCA & Statistical Analysis
Extract meaningful features from processed signals
Deep Learning
CNN/LSTM Networks
Neural networks detect complex patterns and anomalies
Classification
SVM & Random Forest
Classify failure modes and predict remaining useful life
Asset Monitoring
Monitored Assets
Conveyor Belt #7
Conveyor System
Crusher Unit #3
Primary Crusher
Pump Station A
Slurry Pump
Motor Unit #12
Electric Motor
Conveyor Belt #7
WARNINGConveyor System • Processing Plant A
Health Score
mm/s RMS
Current
Days Remaining
AI Prediction
87% confidenceBearing wear detected - replacement recommended within 14 days
Vibration Waveform (Real-time)
Prediction Accuracy
Model Performance
Overall Accuracy
True Positive Rate
Avg. Days Advance
False Alarm Rate
Recent Predictions
Reduction in Unplanned Downtime
Days Advance Warning
Return on Investment
Assets Monitored