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Advisor(s)
Abstract(s)
In the last years we have assisted to several
and deep changes in industrial manufacturing.
Induced by the need of increasing efficiency,
bigger flexibility, better quality and lower costs, it
became more complex [1]. Enterprises had had
the need to cope with market expectations,
incorporating in their production philosophies
new paradigms such as JIT- Just in time, MTOMake
to order, Mass Customization, agile
manufacturing or Lean Manufacturing, that allow
them to satisfy markets with a big diversity of
products and also big quantities, becoming
therefore more competitive. All this complexity
has caused big pressure under enterprises
maintenance systems. Maintenance mission is to
make equipment and facilities available when
requested. Maintenance function, seen as a non
value aggregator one, became more and more
requested to contribute to cost reduction, based
on bigger and consistent equipment reliability.
This perspective is stressed when enterprises
existing equipment has an advanced service life.
It is expected a profusion of breakdowns at those
scenarios and consequently a smaller usability of
equipment driving to less productivity.
From an economic perspective, maintenance
function is seen to the enterprise as a cost [2]. In
fact, experience shows that a major percentage
of the overall costs of the business concerns with
maintenance [3]. Considering this perspective,
decreasing costs with equipment
operationalization will increase maintenance
productivity and consequently overall productivity
[4].
Description
Keywords
Management Maintenance Data mining e-collaboration protocols Reference architectures
Citation
Lopes, Isabel; Pires, Luís; Bastos, Pedro (2010). A decentralized predictive maintenance system based on data mining concepts. In Putnik G. D., Ávila P. (Eds.), First International Conference on Business Sustainability: Management, Technology and Learning for Individuals, Organisations and Society in Turbulent Environments.
Guimarães: University of Minho; Porto: ISEP. p. 254-258. ISBN 978-972-8692-48-3, ISBN 978-989-95907-1-7
Publisher
Universidade do Minho, ISEP