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Research Papers: Pipeline Systems

On the Estimation of Failure Rates of Multiple Pipeline Systems

[+] Author and Article Information
F. Caleyo1

Departamento de Ingeniería Metalúrgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico, Distrito Federal 07738, Mexicofcaleyo@gmail.com

L. Alfonso

Colegio de Ciencia y Tecnología, Universidad Autónoma de la Ciudad de México, Mexico, Distrito Federal 09090, Mexico

J. Alcántara, J. M. Hallen

Departamento de Ingeniería Metalúrgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico, Distrito Federal 07738, Mexico

The Fisher test is strictly valid for the failure truncated case. It is used here for the sake of simplicity, under the assumption that the truncation time is close to the time of the last failure. For the time truncated case, a likelihood ratio test is more appropriate (7).

The term “failure cause” is used in this paper to refer to the actual physical process leading to the failure.

1

Corresponding author.

J. Pressure Vessel Technol 130(2), 021704 (Mar 19, 2008) (8 pages) doi:10.1115/1.2894292 History: Received January 19, 2007; Revised October 16, 2007; Published March 19, 2008

In this work, the statistical methods for the reliability of repairable systems have been used to produce a methodology capable to estimate the annualized failure rate of a pipeline population from the historical failure data of multiple pipeline systems. The proposed methodology provides point and interval estimators of the parameters of the failure intensity function for two of the most commonly applied stochastic models: the homogeneous Poisson process and the power law process. It also provides statistical tests for assessing the adequacy of the stochastic model assumed for each system and testing whether all systems have the same model parameters. In this way, the failure data of multiple pipeline systems are only merged in order to produce a generic failure intensity function when all systems follow the same stochastic model. This allows statistical and tolerance uncertainties to be addressed adequately. The proposed methodology is outlined and illustrated using real-life failure data of oil and gas pipeline systems.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

Grahic Jump Location
Figure 1

Distribution of incidents by (a) system, (b), cause and (c) mode of failure

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Figure 2

Distribution of incidents by cause and total exposure (in km yr) in each system

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Figure 3

Example of reliability deterioration (β>1.0)

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Figure 4

Estimates of the failure rates in the identified pipeline systems due to (a) EC and (b). The failure function of the totality of the gas pipelines is marked as TG.

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