Construction Equipment Predictive Analytics
Implemented predictive maintenance for 200+ excavators, bulldozers, and cranes, reducing breakdowns by 45% and extending equipment lifespan by 20%.
The Challenge
A major construction company with a fleet of 200+ heavy equipment units was experiencing frequent unexpected breakdowns that disrupted project timelines and increased costs. Each breakdown not only meant repair expenses but also project delays and penalties.
The reactive maintenance approach meant that failures often occurred at critical project phases, causing cascading delays and customer dissatisfaction. The company needed a proactive solution to predict and prevent equipment failures.
Key Pain Points
- Frequent unexpected equipment breakdowns
- Project delays costing penalties and reputation damage
- High emergency repair and rental equipment costs
- Shortened equipment lifespan from poor maintenance timing
Our Solution
Health Monitoring Sensors
Installed IoT sensors to track engine hours, hydraulic pressure, temperature, and vibration across all equipment.
AI Failure Prediction
Developed machine learning models to predict component failures 2-3 weeks in advance based on sensor data patterns.
Maintenance Scheduling
Created integrated system to schedule maintenance during equipment downtime, avoiding project disruptions.
Results & Impact
Fewer Breakdowns
Longer Equipment Life
Lower Repair Costs
Additional Benefits
Ready to Prevent Equipment Failures?
Discover how predictive analytics can reduce breakdowns and extend equipment life for your construction fleet.
Get In Touch