Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/13967

TitleSPAMUF: a behaviour-based maintenance prediction system
Author(s)Bastos, Pedro
Lopes, Isabel da Silva
Pires, Luís
KeywordsManagement
Maintenance
Data mining
Knowledge discovery
Issue date2012
PublisherTaylor and Francis
Abstract(s)In the last years we have assisted to several and deep changes in industrial manufacturing. Many industrial processes are now automated in order to ensure the quality of production and to minimize costs. Manufacturing enterprises have been collecting and storing more and more current, detailed and accurate production relevant data. The data stores offer enormous potential as source of new knowledge, but the huge amount of data and its complexity far exceeds the ability to reduce and analyze data without the use of automated analysis techniques. The paper addresses an organizational architecture that integrates data gathered in factories on their activities of reactive, predictive and preventive maintenance. The research is intended to develop a decentralized predictive maintenance system (SPAMUF—Prediction System Failures for Industrial Units Globally Dispersed) based on data mining concepts. Predicting failures more accurately will enable taking appropriate measures to increase reliability.
TypeConference paper
DescriptionAdvances in Safety, Reliability and Risk Management contains the papers presented at the 20th European Safety and Reliability (ESREL 2011) annual conference in Troyes, France, in September 2011.
URIhttp://hdl.handle.net/1822/13967
ISBN978-0-415-68379-1
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:LES/ALG - Textos completos em actas de encontros científicos internacionais com arbitragem

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