Digi > Case Studies > Minimizing Downtime through Predictive Asset Monitoring

Minimizing Downtime through Predictive Asset Monitoring

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 Minimizing Downtime through Predictive Asset Monitoring - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
  • Utilities
Applicable Functions
  • Business Operation
Use Cases
  • Predictive Maintenance
The Customer
About The Customer
Eaton is a power management company providing energy-efficient solutions with approximately 102,000 employees and sells products to customers in more than 175 countries.
The Challenge

It is not a matter if a hydraulic hose will fail, but a matter of when. When hydraulic hoses fail on a garbage truck or on heavy machinery, Eaton's customers spend millions of dollars on hydraulic fluid cleanup, fines, remote service and medical costs that result from injuries.

The Solution

Digi designed a wireless monitoring system to predict hose failure before an issue occurs. By proactively monitoring the health of the hydraulic hoses on widely deployed assets, Eaton was able to extend visibility into their customers’ machine assets. Eaton’s customers can also have real-time access to their machine asset health, uptime, status and alarm thresholds. Software Components - Wireless monitoring system

Data Collected
Alarms For Automated Applications, Asset Performance, Asset Status Tracking, Machine Performance, Uptime
Operational Impact
  • [Efficiency Improvement - Maintenance]
    Real-time status reports enable maintenance personnel to remotely diagnose the status of a device and keep assets running longer.
  • [Efficiency Improvement - Time To Market]
    Downtime tied to breakdowns is minimized due to Digi's solution which accelerate time-to-market .
  • [Data Management - Data Analysis]
    Cloud solutions enable aggregation of 'big data' to enable more robust analysis and lower costs.

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