Predictive Maintenance System
A manufacturing group was experiencing 180+ hours of unplanned downtime annually across its production facilities — each hour costing approximately £11,000 in lost production.
The challenge.
A manufacturing group was experiencing 180+ hours of unplanned downtime annually across its production facilities — each hour costing approximately £11,000 in lost production.
2,000 machines monitored. Failure predicted 72 hours ahead.
The approach.
AurvikAI built an ML predictive maintenance system using sensor data from 2,000+ pieces of equipment. The system detects failure signatures 72 hours before failure occurs — giving the maintenance team time to schedule planned interventions.
The results.
87% reduction in unplanned downtime. £2M annual saving in prevented downtime costs. System now monitoring 2,000+ machines across 4 production facilities. Predictive accuracy of 91% — false alarm rate below 3%.
Reduction in unplanned downtime
Annual savings
Predictive accuracy
False alarm rate
What we used.
Machine Learning · IoT · Manufacturing
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