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Senseye Predictive Maintenance

AI across the full maintenance journey

From reactive repair to prediction and optimization — AI makes equipment health visible in real time.

Senseye Predictive Maintenance
Overview

Senseye is Siemens' predictive maintenance AI solution, covering the full maintenance journey — from reactive repair and condition monitoring to prediction and optimization. It uses AI to analyze equipment data and spot early failure signs, shifting maintenance from "fix when broken" to "act before it fails", improving availability and lowering maintenance cost.

Positioning
Predictive maintenance AI solution
Coverage
Full maintenance lifecycle
Key value
From reactive repair to predictive optimization
Deployment
Cloud / edge
Typical industries
Discrete manufacturing, process, transportation
Key capabilities

Key capabilities

Condition monitoring

Real-time monitoring of equipment health.

Failure prediction

Spot early failure signs and reduce unplanned downtime.

Maintenance optimization

Maintain on demand, reducing over-maintenance.

AI insights

Automated analysis of vibration, temperature and other signals.

What it delivers

What it delivers

  • Fewer unplanned stoppages and higher equipment availability
  • Shift from reactive repair to proactive intervention
  • Lower maintenance and spare-part cost
  • Data-driven maintenance decisions
Modules & components

Modules & components

Data ingestionVibration / temperature / current signal intake.
AI diagnosticsAnomaly detection and root-cause analysis.
PredictionRemaining useful life and failure probability.
Operations integrationLink to maintenance workflows and work orders.
Typical applications

Typical applications

Critical equipment monitoringLine unplanned-downtime preventionSpare-parts planningMaintenance outsourcing decisions

Let’s talk about your project

To move from reactive repair to predictive maintenance, Senseye can help.

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