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research-article

Criticality analysis for maintenance purposes of platform supply vessels in remote areas

[+] Author and Article Information
A. Marhaug

Department of Engineering and Safety UiT The Arctic University of Norway Tromsø, Norway
andreasmarhaug@gmail.com

A. Barabadi

Department of Engineering and Safety UiT The Arctic University of Norway 9037 Tromsø, Norway
abbas.b.abadi@uit.no

E. Stagrum

Leminkäinen Norge 9020 Tromsø, Norway
e_stagrum@hotmail.com

K. Karlsen

Fjellstrand AS 5630 Strandebarm, Norway
ketil.karlsen@hotmail.com

A. Olsen

NPRA Norway 3150 Tolvsrød, Norway
alfmolsen@gmail.com

Y. Z. Ayele

Department of Engineering and Safety UiT The Arctic University of Norway 9037 Tromsø, Norway
yonas.z.ayele@uit.no

1Corresponding author.

ASME doi:10.1115/1.4035304 History: Received September 18, 2016; Revised November 15, 2016

Abstract

The oil and gas industry is pushing towards new unexplored remote areas, potentially rich in resources, but with limited industry presence, infrastructures and emergency preparedness. Maintenance support is very important and challenging in such remote areas. A platform supply vessel (PSV) is an essential part of maintenance support. Hence, the acceptable level of its availability performance is high. Identification of critical components of the PSV provides essential information for optimizing maintenance management, defining a spare parts strategy, estimating competence needs for PSV operation and achieving the acceptable level of availability performance. Currently, there is no standards or guidelines for criticality analysis of PSV for maintenance purposes. In this paper, a methodology for the identification of critical components of PSVs has been developed based on the available standard. It is a systematic screening process. The method considers functional redundancy and the consequences of loss of function as criticality criteria at the main and sub-function levels. Furthermore, at the component level, risk tools such as Failure Modes, Effects and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) will be applied in order to identify the most critical components. Moreover, the application of the proposed approach will be illustrated by a real case study

Copyright (c) 2016 by ASME
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