Failure analysis of a ship’s main engine lubrication system using a dynamic event tree

Αλεξόπουλος, Δημήτριος; Alexopoulos, Dimitrios

dc.contributor.author	Αλεξόπουλος, Δημήτριος	el
dc.contributor.author	Alexopoulos, Dimitrios	en
dc.date.accessioned	2026-02-09T07:43:31Z
dc.date.available	2026-02-09T07:43:31Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/63347
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.31042
dc.rights	Default License
dc.subject	Λίπανση, Κίνδυνος,	el
dc.subject	Κίνδυνος	el
dc.subject	Συντήρηση	el
dc.subject	Αξιοπιστία	el
dc.subject	Κινητήρας	el
dc.title	Failure analysis of a ship’s main engine lubrication system using a dynamic event tree	en
heal.type	bachelorThesis
heal.classification	Naval architecture & Marine engineering	en
heal.language	el
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2025-07-14
heal.abstract	The shipping business is severely tested to ensure the reliability of the propulsion systems of the ship, particularly the main engine lubrication system, which is critical in reducing wear, optimizing performance, and preventing costly failures. This thesis presents a new failure analysis of a ship main engine lubrication system based on a Monte Carlo Dynamic Event Tree (MCDET) approach, implemented in Python, to simulate time-dependent failure behavior for a five-year operating lifetime. Whereas static methods such as Fault Tree Analysis capture only the static failure sequence development, the MCDET approach analyzes component-level failures (e.g., pump, valve, and strainer malfunctions) and system-level hazards (e.g., critical low-pressure value less than 2.5 bar or unwarranted high temperature greater than 81°C) by means of probabilistic safety assessment. 30 run simulation of 2,500 trials each reveals a base-line system failure rate due to cascading reasons such as, mechanical wear and tear, and working stressors in the absence of safety strategies. Periodic maintenance strategies, exposed to intervals between 30 and 360 days, show maximum effectiveness in reducing failure rates, with the best reliability (4.80% system failure rate) and cost-effectiveness being achieved at an interval of 60 days. The model highlights the importance of dynamic risk analysis in maritime systems, supplying failure prediction data and maintenance optimization. Limitations are the absence of main engine data and missing environmental and human factors, hence future research has to be conducted to integrate real-time sensor data, condition monitoring, and human reliability analysis. This effort helps advance maritime risk management for safer and more efficient propulsion systems in terms of compliance with regulations such as SOLAS and MARPOL. Key Words: Monte Carlo Dynamic Event Tree (MCDET), Main Engine Lubrication System, Probabilistic Safety Assessment, Maritime Risk Management, Failure Analysis, Maintenance Optimization, Marine Diesel Engine, System Reliability, Dynamic Risk Assessment.	en
heal.advisorName	Βεντίκος, Νικόλαος	el
heal.committeeMemberName	Ηλιοπούλου, Ελευθερία	el
heal.committeeMemberName	Κονοβέσης, Δημήτριος	el
heal.committeeMemberName	Βεντίκος, Νικόλαος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ναυπηγών Μηχανολόγων Μηχανικών. Τομέας Μελέτης Πλοίου και Θαλάσσιων Μεταφορών	el
heal.academicPublisherID	ntua
heal.numberOfPages	76 σ.	el
heal.fullTextAvailability	false