Manufacturing Leader: Predictive Maintenance
Reduced downtime by 55% with AI-powered predictive maintenance
The Challenge
A leading manufacturing company was experiencing significant production losses due to unplanned equipment downtime. Their reactive maintenance approach was costly and inefficient, with equipment failures causing production delays and expensive emergency repairs.
The manufacturer needed a predictive maintenance solution that could anticipate equipment failures before they occurred, enabling proactive maintenance scheduling.
Our Solution
We implemented an IoT-enabled predictive maintenance system using machine learning
IoT Sensors
Deployed 500+ IoT sensors for real-time monitoring of vibration, temperature, and pressure.
ML Models
Developed anomaly detection and remaining useful life prediction models.
Dashboard
Built real-time monitoring dashboard with automated alert system.
Results
Measurable impact on operational efficiency and cost reduction
Technology Stack
Leveraging industrial IoT and machine learning technologies