Predictive Maintenance System
Client: Manufacturing Industry Leader
enterprise
Project Overview and Challenges
Overview
Developed a predictive maintenance solution to minimize operational disruptions and optimize maintenance schedules for a large manufacturing plant.
Challenges
Unexpected equipment breakdowns were causing significant production losses and high emergency repair costs.
Solution
Deployed IoT sensors to collect real-time equipment data, and used machine learning models to predict potential failures.
Results
Reduced unplanned downtime by 35%, cut maintenance costs by 25%, and extended equipment lifespan by 15%.
Technologies Used
PythonTensorFlowKerasAWS IoTGrafana
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