Optimal spare parts management for vessel maintenance scheduling

Kian, R. ORCID: 0000-0001-8786-6349, Bektaş, T. and Ouelhadj, D., 2019. Optimal spare parts management for vessel maintenance scheduling. Annals of Operations Research, 272 (1-2), pp. 323-353. ISSN 0254-5330

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Abstract

Condition-based monitoring is used as part of predictive maintenance to collect real-time information on the healthy status of a vessel engine, which allows for a more accurate estimation of the remaining life of an engine or its parts, as well as providing a warning for a potential failure of an engine part. An engine failure results in delays and down-times in the voyage of a vessel, which translates into additional cost and penalties. This paper studies a spare part management problem for maintenance scheduling of a vessel operating on a given route that is defined by a sequence of port visits. When a warning on part failure is received, the problem decides when and to which port each part should be ordered, where the latter is also the location at which the maintenance operation would be performed. The paper describes a mathematical programming model of the problem, as well as a shortest path dynamic programming formulation for a single part which solves the problem in polynomial time complexity. Simulation results are presented in which the models are tested under different scenarios.

Item Type: Journal article
Publication Title: Annals of Operations Research
Creators: Kian, R., Bektaş, T. and Ouelhadj, D.
Publisher: Springer
Date: January 2019
Volume: 272
Number: 1-2
ISSN: 0254-5330
Identifiers:
NumberType
10.1007/s10479-018-2907-yDOI
2907Publisher Item Identifier
Rights: © The Author(s) 2018. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Divisions: Schools > Nottingham Business School
Depositing User: Linda Sullivan
Date Added: 18 Sep 2019 14:59
Last Modified: 18 Sep 2019 14:59
URI: http://irep.ntu.ac.uk/id/eprint/37696

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