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Condition monitoring of marine and offshore machinery using evidential reasoning techniques

Asuquo, MP, Wang, J, Phylip-Jones, G and Riahi, R (2019) Condition monitoring of marine and offshore machinery using evidential reasoning techniques. Journal of Marine Engineering and Technology. ISSN 2046-4177

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Abstract

This paper first assesses the operational uncertainties of a particular piece of equipment in a marine and offshore system based on an oil analysis technique. Trend analysis, family analysis, environmental analysis, human reliability analysis and design analysis for each criterion are aggregated using evidential reasoning (ER) and analytical hierarchy process (AHP) algorithms. Data is collected from available statistics and supplemented by expert judgement from the related industry. The results provided in this study will be beneficial to the marine and offshore industries as indicators for monitoring and diagnosis of faults in machinery and thus assist practitioners in making better decisions in their maintenance management process. Furthermore, by changing the conditions that affect the operation of machinery, and through calculating a value for this operation, a benchmark for condition monitoring is constructed. The operational condition of machinery depends on many variables and their dependencies; thus, alteration of a criterion value will ultimately alter the operational conditions of the machinery. For any deviation to be corrected in a timely manner, the operational condition of the machinery has to be monitored properly and frequently.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TC Hydraulic engineering. Ocean engineering
V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions: Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Publisher: Taylor & Francis
Date Deposited: 11 Feb 2019 12:01
Last Modified: 08 Jan 2021 12:19
DOI or Identification number: 10.1080/20464177.2019.1573457
URI: https://researchonline.ljmu.ac.uk/id/eprint/10143

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