Predictive Maintenance and OEE Monitoring for Port Cranes
Montecon / Industrial IoT / Predictive Analytics / Operational Excellence
About
Montecon, the leading operator of public areas in Uruguay, plays a pivotal role in the country's import and export activities. Managing an extensive range of port operations, Montecon is responsible for handling containers, general cargo, and project cargo. Its operations are rooted in efficiency, reliability, and a commitment to facilitating global trade. The cranes, specifically the Gantry cranes (GM), Rubber-Tired Gantry cranes (RTG), and Rail-Mounted Gantry cranes (RMG), are central to Montecon’s operations. These cranes are tasked with the critical job of loading and unloading cargo from ships and strategically moving it within the port area. To continue its leadership in port operations, Montecon emphasizes the importance of employing cutting-edge technology and robust operational strategies to uphold its reputation as one of the most reliable port operators in Uruguay..
Challenge
Montecon’s primary challenge was minimizing the unplanned downtime of their essential cranes, which significantly disrupted port operations and incurred substantial costs. In addition, maintaining peak efficiency of these cranes, critical to overall port productivity, was a persistent goal.
Solution
To navigate these challenges, Montecon introduced a predictive maintenance model and a real-time Overall Equipment Effectiveness (OEE) monitoring system. The predictive maintenance model leverages sensor data from the cranes to anticipate mechanical issues before they become critical, allowing for timely interventions. The real-time OEE monitoring continuously assesses the cranes' performance, availability, and quality, offering instant insights that empower the operations and maintenance teams to act proactively, thereby achieving a highly efficient and data-driven port operation system.
Results
The implementation of the predictive maintenance model and real-time OEE monitoring led to significant operational improvements in Montecon's port operations. One of the most notable outcomes was a 15% increase in Overall Equipment Effectiveness (OEE). This improvement was achieved by leveraging the real-time monitoring capabilities and predictive maintenance model, which enhanced the efficiency of various types of port cranes. Additionally, the predictive model played a crucial role in reducing unplanned downtime by 25%. It enabled timely maintenance activities, thereby substantially decreasing unexpected equipment failures and the associated downtime that interrupts operations. Moreover, the use of predictive insights optimized the maintenance scheduling process, resulting in a 20% improvement in scheduling efficiency. This optimization minimized idle time for the cranes and significantly enhanced the productivity of the maintenance workforce.
+15%
Overall Equipment Effectiveness (OEE)
-25%
Unplanned Downtime
+20%
Maintenance Scheduling Efficiency
The predictive maintenance model and real-time OEE monitoring has transformed the way we manage our port cranes. We are now more proactive, efficient, and our downtime has been minimized substantially. It's a significant step towards our goal of becoming the most efficient port operation in the region.
Diego Suarez
Operations Manager, Montecon
