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Authors: Salvatore Cavalieri and Marco Giuseppe Salafia

Affiliation: University of Catania, Department of Electrical Electronic and Computer Engineering (DIEEI), Viale A. Doria, 6, 95125 Catania, Italy

Keyword(s): Industry 4.0, Asset Administration Shell, Rami 4.0, Predictive Maintenance, Interoperability.

Abstract: Maintenance is one of the most important aspects in industrial and production environment. The availability of huge amount of data coming from sensors and embedded systems, enabled the realisation of Predictive maintenance (PdM). It is an approach that aim to schedule maintenance tasks on the basis of historical data before the occurrence of failures, avoiding machine block downs and reducing the costs due to unnecessary maintenance actions. The adoption of vendor-specific solutions for predictive maintenance and the heterogeneity of technologies adopted in the brownfield for the condition monitoring of machinery reduce the flexibility and interoperability required by Industry 4.0. The paper presents a PdM model leveraging on the Asset Administration Shell (AAS) introduced in Reference Architecture Model for Industrie 4.0 (RAMI 4.0) as a means to enhance interoperability and enabling flexibility and re-configuration of the production against a PdM solution.

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Paper citation in several formats:
Cavalieri, S. and Salafia, M. (2021). Predictive Maintenance Model based on Asset Administration Shell. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-509-8; ISSN 2184-4992, SciTePress, pages 681-688. DOI: 10.5220/0010389306810688

@conference{iceis21,
author={Salvatore Cavalieri. and Marco Giuseppe Salafia.},
title={Predictive Maintenance Model based on Asset Administration Shell},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2021},
pages={681-688},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010389306810688},
isbn={978-989-758-509-8},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Predictive Maintenance Model based on Asset Administration Shell
SN - 978-989-758-509-8
IS - 2184-4992
AU - Cavalieri, S.
AU - Salafia, M.
PY - 2021
SP - 681
EP - 688
DO - 10.5220/0010389306810688
PB - SciTePress

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