Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 93, Issue 2, Pages 234-253Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2006.12.004
Keywords
proactive maintenance; prognosis; degradation; process approach; dysfunctional analysis; dynamic Bayesian network
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The importance of the maintenance function has increased because of its role in keeping and improving system availability and safety, as well as product quality. To support this role, the maintenance concept has undergone several major developments that have led to proactive considerations mainly based on a prognosis process, which normally allows selection of the best maintenance action to be carried out. This paper proposes the deployment and experimentation of a prognosis process within an e-maintenance architecture. The deployment follows a methodology based on the combination of both a probabilistic approach for modelling the degradation mechanism and of an event one for dynamical degradation monitoring. The feasibility and benefits of this new prognosis process is investigated with an experiment using a manufacturing TELMA (TELe-MAintenance) platform supporting the unwinding of metal bobbins. (c) 2007 Elsevier Ltd. All rights reserved.
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