The Main Challenges
About the client
About the client
In this project, the client who operates across the globe in harsh environments wanted to improve equipment maintenance costs. For that, Data Quality was a key issue given the variety of equipment, OEMs, and units and, Artificial Intelligence, was key to supporting decisions on condition-based and predictive maintenance.
Delivering speed to value for their business.
During the project, Intelie impacts their business by significantly reducing maintenance costs. The solution also allowed the increase of revenue generation, by reducing NPT based on equipment failures. We proved that improvement on uptime represents millions of dollars on mid/large-size fleets.
Intelie LIVE has a robust sensor data quality mechanism to enable AI even on heterogeneous plants over satellite communications. Also, advanced algorithms powered by AI and stream analytics were key to identifying anomalous behavior and predicting potential failures. Besides improving maintenance costs, being proactive on maintenance also is a key factor for reducing NPT (Non-Productive Time) and therefore increasing revenue.
The equipment health application was built on top of the Intelie Live platform. It uses the Live-Domain plugin to map the assets hierarchy and also how the sensor's data is related to the assets. The plugin alarms manage the user subscription for each system and also the alarms notification and daily reports. The Live platform is used to create the dashboard visualization and also the alarms.
Equipment Health Monitoring
- With Intelie Live we were able to identify abnormal behavior in real-time and plan the preventive maintenance accordingly (reducing the maintenance cost and also the NPT);
- Integration between the maintenance system and Live enabled the automation of maintenance schedules and automated manual input processes;
- By monitoring in real-time the behavior of equipment we were able to identify degradation over time and also standardize the operation across the fleet;
- The monitoring of fuel consumption and emission is helping the rig operate in a cleaner and efficient manor;
- The standard and scalable data architecture of the Live platform helped the client manage their data through standardized visualizations and rules across the fleet.