Rubix - Implementing Predictive Maintenance
Rubix, a manufacturing SME in the UK, was experiencing frequent equipment breakdowns, resulting in costly downtime and production delays. These unexpected failures were impacting both revenue and customer satisfaction.
The company deployed an AI-powered predictive maintenance system combined with RPA to monitor machinery performance in real-time. The AI algorithms analyzed operational data to predict potential failures before they occurred, while RPA automatically scheduled maintenance tasks and parts ordering when issues were detected.
This implementation reduced unplanned downtime by 40%, extended equipment lifespan, and saved 25% in maintenance costs annually. By shifting from reactive to predictive maintenance, Rubix significantly improved operational reliability and profitability.
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