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Entropy 2015, 17(6), 3656-3678;

A Robust Bayesian Approach to an Optimal Replacement Policy for Gas Pipelines

Departamento de Matematicas, Facultad de Estudios Empresariales y Turismo, Universidad de Extremadura, Avda. Universidad 10003, Cáceres, Spain
Departamento de Matematicas, Facultad de Ciencias, Universidad de Extremadura, Avda. de Elvas 06071, Badajoz, Spain
Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche, Via Bassini 15, I-20133, Milano, Italy
Departamento de Estadistica, Facultad de Ciencias, Universidad de Cádiz, Avda. Polígono Río San Pedro 11510, Puerto Real (Cádiz), Spain
Author to whom correspondence should be addressed.
Academic Editors: Carlos Alberto de Bragança Pereira and Adriano Polpo
Received: 14 March 2015 / Revised: 19 May 2015 / Accepted: 29 May 2015 / Published: 3 June 2015
(This article belongs to the Special Issue Inductive Statistical Methods)
Full-Text   |   PDF [3746 KB, uploaded 3 June 2015]


In the paper, we address Bayesian sensitivity issues when integrating experts’ judgments with available historical data in a case study about strategies for the preventive maintenance of low-pressure cast iron pipelines in an urban gas distribution network. We are interested in replacement priorities, as determined by the failure rates of pipelines deployed under different conditions. We relax the assumptions, made in previous papers, about the prior distributions on the failure rates and study changes in replacement priorities under different choices of generalized moment-constrained classes of priors. We focus on the set of non-dominated actions, and among them, we propose the least sensitive action as the optimal choice to rank different classes of pipelines, providing a sound approach to the sensitivity problem. Moreover, we are also interested in determining which classes have a failure rate exceeding a given acceptable value, considered as the threshold determining no need for replacement. Graphical tools are introduced to help decisionmakers to determine if pipelines are to be replaced and the corresponding priorities. View Full-Text
Keywords: sensitivity analysis; class of priors; non-dominated actions; gas escapes; reliability sensitivity analysis; class of priors; non-dominated actions; gas escapes; reliability
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Arias-Nicolás, J.P.; Martín, J.; Ruggeri, F.; Suárez-Llorens, A. A Robust Bayesian Approach to an Optimal Replacement Policy for Gas Pipelines. Entropy 2015, 17, 3656-3678.

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