Predict Equipment Failures Before They Happen

Real-time fleet health monitoring

Alba combines multi-sensor telemetry, statistical analysis, and machine learning to monitor industrial assets in real time. Detect anomalies early, reduce unplanned downtime, and optimize maintenance schedules across your entire fleet.

Dashboard

Fleet Health

Live

Assets

1,247

Alerts

8

Health

87.3%

Predictions

12

Overall Health87.3%

0%

Downtime Reduction

0

Failures Prevented

$0M

Costs Avoided

0%

ROI Achieved

Core Capabilities

Everything you need to monitor, predict, and prevent equipment failures at scale.

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MMLC Pin Feedback Analysis

Upload SCADA CSV data and run statistical analysis on metal level control pins. Detect anomalies with configurable sigma thresholds, visualize pin command vs. feedback signals, and export detailed reports.

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Multi-Sensor Data Fusion

Correlate temperature, vibration, current, pressure, and RPM data from thousands of sensors across your facility.

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Warning
Alert
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AI-Powered Fault Prediction

Machine learning models predict failures before they occur. Get actionable lead time to plan maintenance.

94% accuracy
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Real-Time Alerting

Severity-based alerts with acknowledge and resolve workflows.

Bearing fault detected
Temperature rising
Maintenance due
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Fleet Health Scoring

Equipment health scores from 0 to 100 with color-coded status across your entire fleet.

Pumps
92%
Motors
78%
Turbines
95%
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ML Model Evaluation

Track precision, recall, and ROC metrics for every predictive model. Validate accuracy continuously.

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Data Quality Monitoring

Sensor uptime heatmaps and missing data tracking ensure reliable, complete datasets.

Seamless Industrial Integration

Connect directly to your existing SCADA, DCS, and control systems. No disruption to operations.

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SCADA
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DCS
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PLC
sensors
Sensors
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Alba Platform

Unified data ingestion

OPC UAModbusMQTT4-20mAHARTProfinet

Real-Time Fleet Intelligence

Monitor every asset across your operations from a single, live dashboard.

Dashboard

Fleet Overview

Live

Assets

1,247

Alerts

8

Health

87.3%

Uptime

99.2%

Health Trend (30 Days)

1007550

Pump P-201

healthy

Compressor C-105

warning

Motor M-442

critical

How It Works

From sensor data to actionable maintenance plans in four steps.

01
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Connect Sensors

Integrate temperature, vibration, current, pressure, and RPM sensors across your industrial assets. Upload SCADA data via CSV or connect live telemetry feeds.

02
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Monitor Assets

Track fleet health in real time with unified dashboards. See health scores, operational status, and telemetry trends for every asset at a glance.

03
troubleshoot

Detect Anomalies

Statistical analysis and machine learning models identify deviations from normal behavior. Configurable sigma thresholds let you fine-tune sensitivity.

04
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Plan Maintenance

Receive severity-based alerts with predicted failure timelines. Prioritize repairs, schedule downtime strategically, and extend asset lifespan.

Monitor Any Industrial Equipment

From rotating machinery to static heat exchangers, Alba covers your full asset fleet.

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Motors

Bearing wearWinding insulation
water_pump

Pumps

CavitationSeal degradation
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Compressors

Valve leakageSurge instability
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Turbines

Blade erosionShaft misalignment
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Gearboxes

Tooth wearLubrication failure
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Conveyors

Belt slippageRoller misalignment
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Fans

ImbalanceBlade cracking
heat

Heat Exchangers

Fouling buildupTube corrosion
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Mixers

Impeller damageSeal leakage

AI-Powered Prediction Engine

Physics-informed AI models analyze vibration signatures, temperature profiles, and electrical patterns to diagnose faults and estimate remaining useful life for every critical asset.

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    Physics-Informed Models

    Combine domain knowledge with data-driven learning for higher accuracy on sparse industrial datasets.

  • troubleshoot

    Fault Diagnosis

    Identify specific failure modes including bearing defects, imbalance, misalignment, and cavitation.

  • schedule

    Remaining Useful Life

    Estimate time-to-failure windows so you can plan maintenance with confidence and precision.

Active Prediction

Pump P-201A

Detected Fault

Bearing Inner Race Defect

Severity

0/10

Confidence

0%

Time to Failure

12-18 days

Contributing Factors

Vibration62%
Temperature24%
Current14%

MMLC Pin Feedback Analysis

The flagship analytical tool for Alba. Upload SCADA CSV exports, configure sigma-based detection thresholds, and instantly identify anomalous pin behavior across your metal level control systems.

Statistical AnalysisSigma-Based DetectionCSV UploadExport Reports

Analysis Output

Processing

Pin Command vs Feedback

Data Points

12,847

Anomalies

23

Detection Rate

96.6%

Ready to transform your maintenance operations?

Join the industrial leaders using Alba to predict failures, reduce downtime, and optimize asset performance.

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