Free Content Formal safety assessment of fishing vessels: risk and maintenance modelling

Authors: Pillay, A.; Wang, J.; Wall, A.; Ruxton, T.; Loughran, C.G.

Source: Proceedings of IMarEST - Part A - Journal of Marine Engineering and Technology, Volume 2004, Number 4, March 2004 , pp. 29-42(14)

Publisher: IMarEST

Buy & download fulltext article:

Free content The full text is free.

View now:
PDF 236.1kb 

Abstract:

Comparisons of the safety record of the fishing industry with other industrial sectors indicate that it continues to be the most dangerous occupation by a significant margin. Satety data from fishing vessels are scarce and often accompanied with a high degree of uncertainty. For this reason the use of conventional probabilistic risk assessment may not be well suited. This paper proposes two novel approaches for risk and maintenance modelling of fishing vessels. An approach using fuzzy set theory (FST) is developed to model the occurrence likelihood and consequences for the identified hazards on a fishing vessel. As the time between maintenance opportunities of a fishing vessel can vary considerably, it allows for failures on the machinery to propagate and lead to a catastrophic breakdown. A model using delay time analysis (DTA) is proposed to ascertain the optimal inspection period for fishing vessel equipment depending on the criteria selected. The two criteria modelled are down time and cost. As both these criteria may not be satisfied simultaneously, a best compromise is proposed. Test data from an ocean going trawler are used to demonstrate the two proposed approaches and the results obtained are discussed in detail.

Document Type: Research article

Publication date: 2004-03-01

More about this publication?
Related content

Tools

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page