Predictive maintenance cutting downtime by 44%
Results at a glance
44%
reduction in unplanned downtime
$9.7M
annual savings
72h
average failure prediction lead time
The Challenge
An industrial manufacturer was experiencing $22M in annual unplanned downtime across 6 production facilities. Maintenance was scheduled on fixed intervals, not actual equipment condition.
What We Built
We integrated IoT sensor data from 840 machines into a centralised data platform, then trained anomaly detection models to predict failures 72 hours in advance. Maintenance teams now receive prioritised work orders through their existing ERP system.
The Results
Project details
Client
Industrial Manufacturer
Industry
Manufacturing
Service
Enterprise AI Integration
Duration
20 weeks
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