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Conference Papers Year : 2021

Health Indicator Modeling and Association Rule Mining for Stoppages Prediction in a Refinery Plant

Abstract

Predictive maintenance practices represent a relevant feature for improving the useful life of the systems and decreasing costs. Hence, the modelling of the Health Indicator is a useful support in order to define the Remaining Useful Life of a system. In this work, an approach for the Health Indicator modeling of an oil refinery sub-plant is proposed; in addition, the Association Rule Mining is applied, in order to identify the components frequently requiring a work order prior to a stoppage of the plant: in this way, the Remaining Useful Life determined via the Health Indicator is used to inspect such components and, possibly, avoid the stoppage.
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Dates and versions

hal-03897856 , version 1 (14-12-2022)

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Attribution - CC BY 4.0

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Giovanni Mazzuto, Sara Antomarioni, Filippo Emanuele Ciarapica, Maurizio Bevilacqua. Health Indicator Modeling and Association Rule Mining for Stoppages Prediction in a Refinery Plant. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.252-260, ⟨10.1007/978-3-030-85914-5_27⟩. ⟨hal-03897856⟩
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