CYIENT > Case Studies > Predictive Analytics Solution for Off Highway Equipment

Predictive Analytics Solution for Off Highway Equipment

 Predictive Analytics Solution for Off Highway Equipment - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Equipment & Machinery
Applicable Functions
  • Maintenance
Use Cases
  • Predictive Maintenance
About The Customer
One of the world’s leading manufacturers of off-highway equipment.
The Challenge

The client wanted to reduce downtime and production losses by effectively prioritizing maintenance activities and proactively replacing components before failure.

The Solution

We designed an ensemble of advanced analytics solutions that could predict when asset components will fail and align replacements with planned maintenance schedules. We also built predictive algorithms, which evaluate a machine’s exception or repair history, operating and maintenance practices, etc. to predict the catastrophic premature failure risk before planned maintenance. We created a predictive model assessing the relative performance of an asset health, ranging from 100 (new) to 0 (failed) based upon the asset risk categories created, to help evaluate the estimated remaining useful life of the asset.

Operational Impact
  • [Management Effectiveness - Operation Transparency]

    Improved management of asset maintenance schedules and performance through executive and asset manager self-service dashboards

  • [Efficiency Improvement - Operation]

    Increased efficiency of scheduling fleet and individual machine maintenance

Quantitative Benefit
  • 8% reduction in maintenance costs

  • 10% reduced asset downtime

  • 13% improvement in overall asset productivity

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