Early Failure Detection of Quayside Container Crane Using the IoT Based Measurement Data

Crane is the important part in a port in ensuring the supply chain management activities, including in Buatan Port, PT. Riau Andalan Pulp and Paper (RAPP). Quayside container crane is used to serve the supply chain activities. The crane consisted of main power supply, hoist system, gantry travel, trolley system and spreader. To maintain the reliability of the crane, the monitoring of those components is necessary. Failures in the hoist system often occur suddenly in the motor component. To improve component reliability, a predictive maintenance approach is proposed by installing IoT-based temperature and vibration measurement devices on the hoist motor, which generate real-time data. To evaluate the system reliability, the failure mode and effects analysis (FMEA) is used by calculating risk priority number (RPN). The RPN would calculate the index based on the severity level, occurrence event probability and detection capability. So that the reliability improvement after applying the predictive maintenance can be presented. As the result the risk level of the crane is reduce from 336 to 144.