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An RCM approach for assessing reliability challenges and maintenance needs of unmanned cargo ships

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  • Eriksen, Stig
  • Utne, Ingrid Bouwer
  • Lützen, Marie

Abstract

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.

Suggested Citation

  • Eriksen, Stig & Utne, Ingrid Bouwer & Lützen, Marie, 2021. "An RCM approach for assessing reliability challenges and maintenance needs of unmanned cargo ships," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    • Handle: RePEc:eee:reensy:v:210:y:2021:i:c:s0951832021001058
    DOI: 10.1016/j.ress.2021.107550
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    References listed on IDEAS

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    1. Wróbel, Krzysztof & Montewka, Jakub & Kujala, Pentti, 2017. "Towards the assessment of potential impact of unmanned vessels on maritime transportation safety," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 155-169.
    2. Mokashi, A. J. & Wang, J. & Vermar, A. K., 2002. "A study of reliability-centred maintenance in maritime operations," Marine Policy, Elsevier, vol. 26(5), pages 325-335, September.
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    Cited by:

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    2. Li, Xue & Oh, Poong & Zhou, Yusheng & Yuen, Kum Fai, 2023. "Operational risk identification of maritime surface autonomous ship: A network analysis approach," Transport Policy, Elsevier, vol. 130(C), pages 1-14.
    3. Yin, Xiuxian & He, Wei & Cao, You & Ma, Ning & Zhou, Guohui & Li, Hongyu, 2024. "A new health state assessment method based on interpretable belief rule base with bimetric balance," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    4. BahooToroody, Ahmad & Abaei, Mohammad Mahdi & Banda, Osiris Valdez & Kujala, Pentti & De Carlo, Filippo & Abbassi, Rouzbeh, 2022. "Prognostic health management of repairable ship systems through different autonomy degree; From current condition to fully autonomous ship," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Yan, R. & Dunnett, S.J. & Jackson, L.M., 2022. "Model-Based Research for Aiding Decision-Making During the Design and Operation of Multi-Load Automated Guided Vehicle Systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    6. Tsoumpris, Charalampos & Theotokatos, Gerasimos, 2023. "A decision-making approach for the health-aware energy management of ship hybrid power plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Fan, Cunlong & Montewka, Jakub & Bolbot, Victor & Zhang, Yang & Qiu, Yuhui & Hu, Shenping, 2024. "Towards an analysis framework for operational risk coupling mode: A case from MASS navigating in restricted waters," Reliability Engineering and System Safety, Elsevier, vol. 248(C).

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