Comparative reliability analysis and enhancement of marine dual-fuel engines

Giorgos Lazaridis Kirolivanos, Byongug Jeong

Research output: Contribution to journalArticlepeer-review

Abstract

This paper was to examine the reliability and criticality of two dual-fuel marine engine systems and to compare them with a conventional diesel engine system with the utilization of the dynamic fault tree analysis. The scope of analysis holistically ranges from the engines sets to their auxiliary systems. The results of reliability analysis for the dual-fuel engines indicate that the failure probability of the dual-fuel engine is 8.84% on average at 14,000 running hours whereas 8.48% for the diesel engines. This finding contrasts our intuition that the dual-fuel engines are of higher risk compared to the conventional diesel engines. Research findings, obtained from the reliability-centered maintenance, also suggest an effective way of enhancing the safety of engine systems through predictive maintenance, based on the periodical maintenance of critical components. Therefore, it can contribute to improving the reliability of the whole systems in which mechanical components and fuel oil feed systems were identified as critical elements to diminish the system reliability significantly. It also highlights the importance of the proper maintenance of system components that would greatly enhance the safety levels by restoring systems back to their original operating condition, hence minimizing downtime and operating costs. Lastly, the research outputs also offer meaningful insights into shipping companies about the association between the planned maintenance strategies and the system reliability.
Original languageEnglish
JournalJournal of International Maritime Safety, Environmental Affairs, and Shipping
DOIs
Publication statusAccepted/In press - 10 Aug 2021

Keywords

  • Dynamic Fault Tree Analysis (DFTA)
  • marine industry
  • two-stroke dual-fuel engines
  • two-stroke diesel engines
  • data analysis
  • safety
  • maintenance
  • predictive maintenance
  • reliability
  • criticality

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