Reliability Methods in Maintenance and Failure Analysis of Marine Systems

Weibull analysis hidden Markov models (HMM) preventive maintenance predictive maintenance system reliability technical logistics

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This paper explores the application of advanced analytical methods and predictive maintenance technologies to optimise maintenance strategies for complex technical systems, with a specific focus on marine engines and high-pressure fuel pumps. Weibull analysis facilitated the identification of failure patterns and precise planning of maintenance intervals, while hidden Markov models (HMM) provided deeper insights into the dynamics of state transitions, such as degradation and failure. The results demonstrate that combining reliability theory with cost analysis ensures an optimal balance between maintenance costs and system reliability. HMM revealed how changes in pump performance directly impact engine functionality, whereas failure data alone often fail to provide a clear understanding of system conditions. Integrating HMM enabled better comprehension of underlying processes, which is crucial for aligning pump maintenance with reduced failure rates and improved operational efficiency. The application of these methods and technologies reduces maintenance costs, extends equipment lifespan and enhances overall efficiency. System safety is ensured, and the risk of unexpected failures is minimised, contributing to the stability and economic sustainability of complex technical systems. This integrated approach offers a framework for future maintenance strategies, uniting technical and financial aspects into a comprehensive solution for long-term reliability and effectiveness.