Penerapan Metode Mean Time Between Failure dan Mean Time to Repair dalam Pemeliharaan Prediktif Mesin Compressor Kobelco Dengan Integrasi Sistem Monitoring Berbasis Internet of Things (Iot) di PT Suzuki Indomobil Motor

Abstract

Predictive maintenance is an important strategy in maintaining optimal industrial machine performance. This study aims to apply the Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR) methods as analysis tools in the predictive maintenance system of the Kobelco Compressor machine at PT Suzuki Indomobil Motor. By integrating an Internet of Things (IoT)-based monitoring system, machine operational data can be collected and analyzed in real-time to detect potential damage before a functional failure occurs. This method helps in determining more accurate and efficient maintenance time intervals. The results of the study show that the use of MTBF and MTTR integrated with the IoT system can increase maintenance effectiveness, reduce machine downtime, and support data-based decision making. This implementation is expected to increase operational efficiency and reliability of the overall production system.