Asuquo, MP (2018) Development of an Efficient Planned Maintenance Framework for Marine and Offshore Machinery Operating under Highly Uncertain Environment. Doctoral thesis, Liverpool John Moores University.

Preview

Text 2017mauricephd.pdf - Published Version Download (4MB) | Preview

Abstract

The constantly increasing complexity of marine and offshore machinery is a consequence of a constant improvement in ship powering, automation, specialisation in cargo transport, new ship types, as well as an effort to make the sea transport more economic. Therefore, the criteria of reliability, availability and maintainability have become very important factors in the process of marine machinery design, operation and maintenance. An important finding from the literature exposed that failure to marine machinery can cause both direct and indirect economic damage with a long-term financial consequence. Notably, many cases of machinery failures reported in databases were as a result of near misses and incidents which are potential accident indicators. Moreover, experience has shown that modelling of past accident events and scenarios can provide insights into how a machinery failure can be subsisted even if it is not avoidable, also a basis for risk analysis of the machinery in order to reveal its vulnerabilities. This research investigates the following modelling approach in order to improve the efficiency of marine and offshore machinery operating under highly uncertain environment. Firstly, this study makes full use of evidential reasoning’s advantage to propose a novel fuzzy evidential reasoning sensitivity analysis method (FER-SAM) to facilitate the assessment of operational uncertainties (trend analysis, family analysis, environmental analysis, design analysis, and human reliability analysis) in ship cranes. Secondly, a fuzzy rule based sensitivity analysis methodology is proposed as a maintenance prediction model for oil-wetted gearbox and bearing with emphasis on ship cranes by formulating a fuzzy logic box (diagnostic table), which provides the ship crane operators with a means to predict possible impending failure without having to dismantle the crane. Thirdly, experience has shown that it is not financially possible to employ all the suggested maintenance strategies in the literature. Thus, this study proposed a fuzzy TOPSIS approach that can help the maintenance engineers to select appropriate strategies aimed at enhancing the performance of the marine and offshore machinery. Finally, the developed models are integrated in order to facilitate a generic planned maintenance framework for robust improvement and management, especially in situations where conventional planned maintenance techniques cannot be implemented with confidence due to data deficiency.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Condition Monitoring; Analytical Hierarchy Process; Evidential Reasoning; Planned Maintenance; Risk Assessment; Machinery Reliability; Rule Based; Machinery Oil Analysis; Maintenance Strategy; Multi-Attribute Group Decision Making; TOPSIS; Trend Analysis; Family Analysis; Environmental Analysis; Human Reliability Analysis; Design Analysis
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management T Technology > TJ Mechanical engineering and machinery V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Date Deposited:	14 May 2018 09:41
Last Modified:	23 Nov 2022 09:49
DOI or ID number:	10.24377/LJMU.t.00008614
Supervisors:	Wang, J, Phylip-Jones, G and Zhang, L
URI:	https://researchonline.ljmu.ac.uk/id/eprint/8614

View Item