Predictive Maintenance
Reduce downtime, lowers costs, enhances safety, and extends equipment lifespan by detecting failures before they occur.
ABOUT OUR WORK
Traditional maintenance relied on fixed schedules or reactive repairs, often resulting in unexpected breakdowns, high costs, and safety risks. These methods lacked real-time insight and couldn’t scale across complex industrial systems.
Our AI-based maintenance system uses drone inspections and deep learning to detect issues early and reduce downtime. Models process thermal and visual data to identify corrosion, leaks, and structural faults. Integration with CMMS automates workflows and improves asset lifecycle management. This boosts uptime, lowers inspection costs, and enhances safety.
IF YOU WANT THE SPECIFICS
25% more uptime – AI predicts failures early and keeps equipment running smoother, longer.
ARCHITECTURE
AI-powered drones with LiDAR and thermal imaging inspect assets in real time for signs of wear, corrosion, or leaks. Deep learning models like YOLOv8 and Faster R-CNN detect faults and trigger predictive maintenance actions. Integration with CMMS automates repair scheduling and resource allocation.
KEY CONSIDERATIONS
The system connects to IoT platforms and maintenance tools like SAP PM and Maximo through secure APIs. Edge processing allows local anomaly detection with minimal latency. It’s designed for safety-critical environments like oil & gas facilities and heavy industry.
