The effectiveness and safety of crude oil barging transportation is largely dependent on inland waterway transportation and the engaged mechanical systems. Mechanical systems breakdowns and logistical delays deter performance of tugboat propulsion systems. To improve the efficiency of crude oil barging operations, this study explored reliability analysis of tugboat propulsion components. Predictive maintenance methods, reliability engineering tools, and failure data analytics were jointly considered in a quantitative, exploratory-descriptive research approach. In this study, critical failure modes spanning shaft lines, couplings, and gear assemblies were identified and ranked using Failure Modes and Effects Analysis (FMEA). While, most parameters used for reliability measures such as Mean Time Between Failures (MTBF), Mean Time To Repair (MTTR), and system availability were analyzed using ReliaSoftBlockSim and Weibull analysis, the correlation and root cause analysis approach were applied in the determination of the connections between component failures and important operational variables involving barge turnaround time, tug availability, fuel consumption, and mission delays.

The key results of the study showed that failure of mechanical components leads to unscheduled operations downtime. The research offers a strong and significant performance improvement using redundancy and managing maintenance interval, in providing a data-driven roadmap for incorporating Reliability-Centered Maintenance (RCM) into marine logistics, especially in inland crude oil transportation operations. In addition, .a predictive maintenance framework based on vibration analysis, oil debris detection, and infrared thermography were handled using condition monitoring data.