RT info:eu-repo/semantics/article
T1 The asset administration shell as enabler for predictive maintenance: a review
A1 Rahal, Jhonny Rodriguez
A1 Schwarz, Alexander
A1 Sahelices, Benjamín
A1 Weis, Ronny
A1 Antón, Simon Duque
K1 Asset administration shell
K1 Predictive maintenance
K1 Digital twin
K1 Machine learning
K1 Industry 4.0
K1 WaVe
AB The emergence of the Internet of Things and the interconnection of systems and machines enables the idea of Industry 4.0, a new industrial paradigm with a strong focus on interaction and communication between physical and digital entities, leading to the creation of cyber-physical systems. The digital twin and the standard for the Asset Administration Shell are concepts derived from Industry 4.0 that exploit the advantages of connecting the physical and virtual domains, improving the management and display of the collected data. Furthermore, the increasing availability of data has enabled the implementation of data-driven approaches, such as machine and deep learning models, for predictive maintenance in industrial and automotive applications. This paper provides a two-dimensional review of the Asset Administration Shell and data-driven methods for predictive maintenance, including fault diagnosis and prognostics. Additionally, a digital twin architecture combining the Asset Administration Shell, predictive maintenance and data-driven methods is proposed within the context of the WaVe project.
PB SPRINGER LINK
SN 0956-5515
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/66171
UL https://uvadoc.uva.es/handle/10324/66171
LA spa
NO Journal of Intelligent Manufacturing
NO Producción Científica
DS UVaDOC
RD 22-dic-2024