- Analytics & Modeling - Predictive Analytics
- Equipment & Machinery
- Predictive Maintenance
The client wanted to reduce downtime and production losses by effectively prioritizing maintenance activities and proactively replacing components before failure.
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.
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