Predictive Maintenance
Employ a product-centric approach to servicing equipment
Use artificial intelligence models to predict machine downtime, schedule proactive maintenance, predict time to action for equipment requiring replenishment/replacement and other advanced data-enabled features

Identify impending faults early and help reduce costly emergency repairs
Predict when a component will fail and proactively schedule maintenance plans
Identify failure of an asset with longer lead time to improve reliability and performance
Drive mission-critical decisions such as which spare parts to replace
Reduce the number and cost of service truck rolls
Analyze event data from devices to identify trends, patterns and predictions
Resources about
Predictive Maintenance
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Case Study: HVACR Analytics
Unlock the value of HVACR sensor data with mnubo’s IoT analytics & data science library’s
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Industrial IoT Insight: Asset Health Score
Asset Health Scores empower service teams with enhanced real-time visibility over the products connected life
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