EOT Crane Maintenance and Fault Detection Case Study

This case study focuses on the application of PlantOS™ technology in monitoring the main hoist of an EOT crane within a steel melt shop. It outlines the challenges faced by maintenance teams who typically perform standard checks but may overlook critical failure signs, such as the gradual degradation of motor bearings. The study details how PlantOS™ detected a rising vibration signature 90 days before a potential failure, allowing for a scheduled maintenance intervention rather than an emergency shutdown. The document presents measured outcomes, including a significant reduction in unplanned downtime and improved operational reliability. It describes the continuous monitoring process, the prescriptive AI engine's role in diagnosing issues, and the corrective actions taken to resolve the bearing looseness without affecting production throughput. The case study illustrates the effectiveness of predictive maintenance strategies in enhancing crane availability and operational efficiency.