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Authors: Qiushi Cao 1 ; Ahmed Samet 2 ; Cecilia Zanni-Merk 1 ; François Bertrand de de Beuvron 2 and Christoph Reich 3

Affiliations: 1 Normandie Université/INSA Rouen, LITIS, 76000 Saint- Étienne-du-Rouvray, France ; 2 ICUBE/SDC Team (UMR CNRS 7357)-Pole API BP 10413, 67412 Illkirch, France ; 3 Hochschule Furtwangen, 78120 Furtwangen, Germany

Keyword(s): Industry 4.0, Predictive Maintenance, Ontologies, SWRL Rules, Evidential Clustering.

Abstract: In smart factories, machinery faults and failures are detrimental to the efficiency and reliability of production systems. To ensure the smooth operation of production systems, predictive maintenance techniques have been widely used in a variety of contexts. In this paper, we tackle the machinery failure prediction task by introducing a novel hybrid ontology-based approach. The proposed approach is based on the combined use of evidential theory tools and semantic technologies. Among evidential theory tools, the Evidential C-means (ECM) algorithm is used to assess the criticality of failures according to two main parameters (time constraints and maintenance cost). In addition, domain ontologies with their rule-based extensions are used to formalize the domain knowledge and predict the time and criticality of future failures. Case studies on synthetic data sets and a real-world data set are used to validate the proposed approach.

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Paper citation in several formats:
Cao, Q.; Samet, A.; Zanni-Merk, C.; de Beuvron, F. and Reich, C. (2020). Combining Evidential Clustering and Ontology Reasoning for Failure Prediction in Predictive Maintenance. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-395-7; ISSN 2184-433X, SciTePress, pages 618-625. DOI: 10.5220/0008969506180625

@conference{icaart20,
author={Qiushi Cao. and Ahmed Samet. and Cecilia Zanni{-}Merk. and Fran\c{C}ois Bertrand de {de Beuvron}. and Christoph Reich.},
title={Combining Evidential Clustering and Ontology Reasoning for Failure Prediction in Predictive Maintenance},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2020},
pages={618-625},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008969506180625},
isbn={978-989-758-395-7},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Combining Evidential Clustering and Ontology Reasoning for Failure Prediction in Predictive Maintenance
SN - 978-989-758-395-7
IS - 2184-433X
AU - Cao, Q.
AU - Samet, A.
AU - Zanni-Merk, C.
AU - de Beuvron, F.
AU - Reich, C.
PY - 2020
SP - 618
EP - 625
DO - 10.5220/0008969506180625
PB - SciTePress

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