Lopes, Isabel S.Pires, LuísBastos, Pedro2012-07-132012-07-132010Lopes, 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 978-989-95907-1-7978-972-8692-48-3978-989-95907-1-7http://hdl.handle.net/10198/7208In 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].engManagementMaintenanceData mininge-collaboration protocolsReference architecturesconference object