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2021 | OriginalPaper | Buchkapitel

AutomationML in Industry 4.0 Environment: A Systematic Literature Review

verfasst von : Jiaqi Zhao, Matthias Schamp, Steven Hoedt, El-Houssaine Aghezzaf, Johannes Cottyn

Erschienen in: Advances in Automotive Production Technology – Theory and Application

Verlag: Springer Berlin Heidelberg

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Abstract

AutomationML is an open neutral XML based data exchange format used in automation systems. It has come into the public for more than 10 years and is being used in many different areas in all kinds of manufacturing applications, such as digital twin, reconfigurable manufacturing systems, heterogeneous data exchange, etc. However, no comprehensive literature review on the research and application progress of AutomationML has been found since the initiation of AutomationML. Based on the study and analysis of AutomationML related publications, this paper gives a detailed illustration on the state-of-the-art of AutomationML. Firstly, the background and terminologies related to AutomationML are introduced. Secondly, the paper applies a methodology to collect AutomationML related publications, on which an analysis based on a multidimensional literature classification is conducted. Thirdly, according to the analysis results, current research status and whether AutomationML can meet the requirements for industry 4.0 environment are discussed. Finally, conclusion and outlook are illustrated in the end.

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Vorheriges Kapitel Assets2036 – Lightweight Implementation of the Asset Administration Shell Concept for Practical Use and Easy Adaptation

Nächstes Kapitel Generic and Scalable Modeling Technique for Automated Processes

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Titel: AutomationML in Industry 4.0 Environment: A Systematic Literature Review
verfasst von: Jiaqi Zhao
Matthias Schamp
Steven Hoedt
El-Houssaine Aghezzaf
Johannes Cottyn
Verlag: Springer Berlin Heidelberg
Buch: Advances in Automotive Production Technology – Theory and Application
Print ISBN: 978-3-662-62961-1

Electronic ISBN: 978-3-662-62962-8

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-662-62962-8_19

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