An integration of multi-criteria decision making techniques with a delay time model for determination of inspection intervals for marine machinery systems
An integration of multi-criteria decision making techniques with a delay time model for determination of inspection intervals for marine machinery systems
For certain critical equipment items in marine machinery systems, the optimum maintenance strategy would be a scheduled on-condition operation. This involves inspection of the equipment items in order to monitor their performance degradation and, invariably, carry out repair or replacement tasks. The main challenge with this type of maintenance approach is the determination of the appropriate interval for performing the inspection task. This paper presents a methodology which integrates multi-criteria decision making (MCDM) tools with a delay time model for the determination of optimum inspection intervals for marine machinery systems. With this approach, multiple decision criteria are modelled with the delay time concept and aggregated with MCDM tools such that different criteria can be applied simultaneously in the ranking of different inspection interval alternatives. The applicability of the proposed methodology is demonstrated using the case study of a water cooling pump of the central cooling system of a marine diesel engine.
Criteria, Decision, Delay time model, ELECTRE, Expected company reputation, Expected cost, Expected downtime, Inspection interval, Marine machinery systems, MAUT
65-82
Emovon, Ikuobase
e0a51526-6e06-4c29-ba98-6ea531cee694
Norman, Rosemary A.
6d2518aa-ece8-498f-82dc-dee5ec7b1b37
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
2 June 2016
Emovon, Ikuobase
e0a51526-6e06-4c29-ba98-6ea531cee694
Norman, Rosemary A.
6d2518aa-ece8-498f-82dc-dee5ec7b1b37
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
Emovon, Ikuobase, Norman, Rosemary A. and Murphy, Alan J.
(2016)
An integration of multi-criteria decision making techniques with a delay time model for determination of inspection intervals for marine machinery systems.
Applied Ocean Research, 59, .
(doi:10.1016/j.apor.2016.05.008).
Abstract
For certain critical equipment items in marine machinery systems, the optimum maintenance strategy would be a scheduled on-condition operation. This involves inspection of the equipment items in order to monitor their performance degradation and, invariably, carry out repair or replacement tasks. The main challenge with this type of maintenance approach is the determination of the appropriate interval for performing the inspection task. This paper presents a methodology which integrates multi-criteria decision making (MCDM) tools with a delay time model for the determination of optimum inspection intervals for marine machinery systems. With this approach, multiple decision criteria are modelled with the delay time concept and aggregated with MCDM tools such that different criteria can be applied simultaneously in the ranking of different inspection interval alternatives. The applicability of the proposed methodology is demonstrated using the case study of a water cooling pump of the central cooling system of a marine diesel engine.
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More information
Accepted/In Press date: 12 May 2016
e-pub ahead of print date: 2 June 2016
Published date: 2 June 2016
Additional Information:
Funding Information:
The authors would like to thank the Federal University of Petroleum resources , Effurun, Nigeria for funding this research through the TETFUND academic staff training intervention fund . They would also like to thank the School of Marine Science and Technology , Newcastle University, United Kingdom for providing the enabling environment for conducting this research.
Keywords:
Criteria, Decision, Delay time model, ELECTRE, Expected company reputation, Expected cost, Expected downtime, Inspection interval, Marine machinery systems, MAUT
Identifiers
Local EPrints ID: 483826
URI: http://eprints.soton.ac.uk/id/eprint/483826
ISSN: 0141-1187
PURE UUID: ddfac882-ee64-4e36-bbb5-fd9207d4acc6
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Date deposited: 06 Nov 2023 18:19
Last modified: 10 May 2024 17:03
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Contributors
Author:
Ikuobase Emovon
Author:
Rosemary A. Norman
Author:
Alan J. Murphy
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