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Failure rate prediction with artificial neural networks

Maurizio Bevilacqua (Dipartimento di Ingegneria delle Costruzioni Meccaniche, Nucleari, Aeronautiche e di Metallurgia, Università degli Studi di Bologna, Bologna, Italy)
Marcello Braglia (Dipartimento di Ingegneria delle Costruzioni Meccaniche, Nucleari, Aeronautiche e di Metallurgia, Università degli Studi di Bologna, Bologna, Italy)
Marco Frosolini (Dipartimento di Ingegneria Meccanica, Nucleare e della Produzione, Università di Pisa, Pisa, Italy)
Roberto Montanari (Dipartimento di Ingegneria Industriale, Università degli Studi di Parma, Parma, Italy)

Journal of Quality in Maintenance Engineering

ISSN: 1355-2511

Article publication date: 1 September 2005

1645

Abstract

Purpose

To suggest that a multi layer perception based artificial neural network (MLP‐ANN) is a practical instrument to evaluate the expected failure rates of 143 centrifugal pumps used in an oil refinery plant.

Design/methodology/approach

A MLP is adopted to weigh up the correlation existing among the failure rates and the several different operating conditions which have some influence in the occurrence.

Findings

During the training phase, it is possible to discriminate among those variables closely significant for the final outcome and those which can be kept off from the analysis. In particular, the neural network automatically calculates and classifies the centrifugal pumps in terms of both the failure probability and its variability degree, giving a better analysis instrument to take decisions and to justify them, in order to optimise and fully support an eventual preventive maintenance (PM) program.

Originality/value

Aids in decision‐making to reduce the necessity of reactive maintenance activities and to simplify the planning of PM ones.

Keywords

Citation

Bevilacqua, M., Braglia, M., Frosolini, M. and Montanari, R. (2005), "Failure rate prediction with artificial neural networks", Journal of Quality in Maintenance Engineering, Vol. 11 No. 3, pp. 279-294. https://doi.org/10.1108/13552510510616487

Publisher

:

Emerald Group Publishing Limited

Copyright © 2005, Emerald Group Publishing Limited

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