Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/26189

TitleApplication of data mining in a maintenance system for failure prediction
Author(s)Bastos, Pedro
Lopes, Isabel da Silva
Pires, Luís
Issue date2014
PublisherTaylor & Francis
Abstract(s)In industrial environment, data generated during equipment maintenance and monitoring activities has become increasingly overwhelming. Data mining presents an opportunity to increase significantly the rate at which the volume of data can be turned into useful information. This paper presents an architecture designed to gather data generated in industrial units on their maintenance activities, and to forecast future failures based on data analysis. Rapid Miner is used to apply different data mining prediction algorithms to maintenance data and compare their accuracy in the discovery of patterns and predictions. The tool is integrated with an online system which collects data using automatic agents and presents all the results to the maintenance teams. The purpose of the prediction algorithms is to forecast future values based on present records, in order to estimate the possibility of a machine breakdown and therefore to support maintenance teams in planning appropriate maintenance interventions.
TypeConference paper
DescriptionPublicado em : "Safety, reliability and risk analysis : beyond the horizon", ISBN 978-1-138-00123-7
URIhttp://hdl.handle.net/1822/26189
ISBN9781138001237
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:LES/ALG - Textos completos em actas de encontros científicos internacionais com arbitragem

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