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Reliability prediction of offshore oil and gas equipment for use in an arctic environment

Rahimi, Maryam and Rausand, Marvin and Wu, Shaomin (2011) Reliability prediction of offshore oil and gas equipment for use in an arctic environment. In: 2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering. IEEE. ISBN 978-1-4577-1229-6. E-ISBN 978-1-4577-1232-6. (doi:10.1109/ICQR2MSE.2011.5976574) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:65460)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/ICQR2MSE.2011.5976574

Abstract

The offshore oil and gas industry is currently moving into the arctic region. The harsh arctic environment will have an unavoidable influence on the reliability of the equipment operated in it. To understand this influence is of vital importance to ensure the reliability of the equipment and the production availability of the systems. Several types of data, such as data on design, production, usage intensity, and operating environment are required to assess and verify the reliability of the equipment. This paper proposes a framework for reliability assessment based on proportional hazards modeling and various types of data. It presents important arctic factors influencing the physical performance and discusses how these may influence the reliability of the equipment.

Item Type: Book section
DOI/Identification number: 10.1109/ICQR2MSE.2011.5976574
Uncontrolled keywords: reliability; arctic; ice; data models; ocean temperature; meteorology; hazards
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 14 Dec 2017 16:27 UTC
Last Modified: 16 Nov 2021 10:24 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/65460 (The current URI for this page, for reference purposes)

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