Unmanned autonomous cargo ships may change the maritime industry, but there are issues regarding reliability and maintenance of machinery equipment that are yet to be solved. This article examines the applicability of the Reliability Centred Maintenance (RCM) method for assessing maintenance needs and reliability issues on unmanned cargo ships. The analysis shows that the RCM method is generally applicable to the examination of reliability and maintenance issues on unmanned ships, but there are also important limitations. The RCM method lacks a systematic process for evaluating the effects of preventive versus corrective maintenance measures. The method also lacks a procedure to ensure that the effect of the length of the unmanned voyage in the development of potential failures in machinery systems is included. Amendments to the RCM method are proposed to address these limitations, and the amended method is used to analyse a machinery system for two operational situations: one where the vessel is conventionally manned and one where it is unmanned. There are minor differences in the probability of failures between manned and unmanned operation, but the major challenge relating to risk and reliability of unmanned cargo ships is the severely restricted possibilities for performing corrective maintenance actions at sea.
The power system of an all-electric ship (AES) establishes an independent microgrid using the distributed energy resources, energy storage devices, and power electronic converters. As a hybrid energy system (HES), the power system of an AES works as a unified system where each part can affect the reliability of the other parts. The systemic reliability centered maintenance (SRCM), which efficiently enhances the reliability and safety of the AES by identifying optimal maintenance tasks of the AES, is considered in this article to apply to the entire system. In order to calculate the reliability and optimal maintenance schedule, the Markov process and Enhanced JAYA (EJAYA) are utilized. A layer of protection analysis (LOPA), which is a risk management technique, is adopted to assess the safety of the system. A hybrid molten carbonate fuel cell, photovoltaic (PV), and lithium-ion battery are considered as energy sources of the AES. Based on two common standards, DNVGL-ST-0033 and DNVGL-ST-0373, the suggested maintenance planning method can be used in industrial applications. Eventually, in order to validate the proposed method, a model-in-the-loop real-time simulation using dSPACE is carried out. The obtained results show the applicability and efficiency of the proposed method for improving reliability and safety.