Model adaptacyjnego algorytmu wspomagania decyzji w systemie utrzymania ruchu
Journal Title: Zarządzanie Przedsiębiorstwem - Year 2016, Vol 0, Issue 4
Abstract
Currently used predictive maintenance systems predict future events by monitoring residual processes using the enforced predictive model. Despite the benefits resulting from their implementation in companies (e.g. savings resulting from preventing failure), it is necessary to draw attention to the fact that such models lack flexibility in adapting to the dynamically changing values of observation vectors due to real-time readout which can provide more accurate predictions. The paper proposes a model of adaptive algorithm for maintenance decision support system which depending on the changing parameters of residual processes selects an adequate mathematical model based on predictive and informative criteria. Moreover, to produce more accurate predictions this model uses additional input data for prediction including values of residual processes as well as technical or quality-related aspects due to the extended range of observed factors that affect failure occurrence. The proposed model additionally contains a maintenance decision-related part which based on the information about actions taken by maintenance services generates a constrained optimal time interval for performing the necessary maintenance work.
Authors and Affiliations
E. Kosicka, D. Mazurkiewicz, A. Gola
Keywords
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- EP ID EP352938
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