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at - Automatisierungstechnik

Methoden und Anwendungen der Steuerungs-, Regelungs- und Informationstechnik

[AT - Automation Technology: Methods and Applications of Control, Regulation, and Information Technology

Editor-in-Chief: Jumar, Ulrich

IMPACT FACTOR 2017: 0.503

CiteScore 2017: 0.47

SCImago Journal Rank (SJR) 2017: 0.212
Source Normalized Impact per Paper (SNIP) 2017: 0.546

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Volume 66, Issue 10


Model-based generation of run-time data collection systems exploiting AutomationML

Modellbasierte Generierung von Laufzeit-Datenerfassungssystemen aus AutomationML

Alexandra Mazak / Arndt Lüder / Sabine Wolny / Manuel Wimmer / Dietmar Winkler / Konstantin Kirchheim / Ronald Rosendahl / Hessamedin Bayanifar / Stefan Biffl
Published Online: 2018-10-17 | DOI: https://doi.org/10.1515/auto-2018-0022


Production system operators need support for collecting and pre-processing data on production systems consisting of several system components, as foundation for optimization and defect detection. Traditional approaches based on hard-coded programming of such run-time data collection systems take time and effort, and require both domain and technology knowledge. In this article, we introduce the AML-RTDC approach, which combines the strengths of AutomationML (AML) data modeling and model-driven engineering, to reduce the manual effort for realizing the run-time data collection (RTDC) system. We evaluate the feasibility of the AML-RTDC approach with a demonstration case about a lab-sized production system and a use case based on real-world requirements.


Betreiber von Produktionsstätten benötigen Unterstützung beim Sammeln und Vorverarbeiten von Daten über die Laufzeit von Produktionssystemen, die aus mehreren Systemkomponenten bestehen. Hauptsächlich nutzen die Betreiber diese Informationen als Grundlage für die Optimierung der Anlagen und zur Fehlererkennung. Herkömmliche Ansätze von sogenannten Laufzeitdaten-Erhebungssystemen basieren zumeist auf hartcodierter Programmierung, die neben manuellem und zeitlichem Aufwand auch Domänenwissen und entsprechendes Technologie-Knowhow erfordern.

In diesem Artikel führen wir den AML-RTDC-Ansatz ein, der die Stärken der AutomationML Datenmodellierung mit der modellgetriebenen Systementwicklung kombiniert, um den manuellen und zeitlichen Aufwand beim Entwerfen eines Laufzeitdaten-Erhebungssystems zu minimieren. Wir evaluieren die Realisierbarkeit dieses Ansatzes anhand einer Fallstudie basierend auf einem Laborproduktionssystem und einem Anwendungsfall, der auf realen Anforderungen basiert.

Keywords: model-driven engineering; AutomationML; OPC UA; runtime monitoring; anomaly detection

Schlagwörter: Modellgetriebene Entwicklung; AutomationML; OPC UA; Laufzeitüberwachung; Anomalieerkennung


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About the article

Alexandra Mazak

Dipl-Ing. Mag. Dr. techn. Alexandra Mazak is a senior researcher at the Business Informatics Group and in the Christian Doppler Laboratory for Model-Integrated Smart Production (CDL-MINT) at TU Wien. Her research interests comprise data integration, statistical modeling and forecast as well as model-driven systems and software engineering in the research field of Industry 4.0. She headed numerous national funded projects in this research field. For more information, please visit http://www.big.tuwien.ac.at/staff/amazak.

Arndt Lüder

Apl. Prof. Dr.-Ing. habil. Arndt Lüder attended the Otto-von-Guericke University at Magdeburg, Germany. He worked at Otto-von-Guericke-University Magdeburg and Martin-Luther-University Halle-Wittenberg in the field of formal methods for control system design. Since 2001 he has been working at the Center of Distributed Systems within the Faculty Mechanical Engineering at Otto-von-Guericke-University Magdeburg. Since 2006 he has been the head of this center. He was promoted to professor in 2007 on “Distributed Control Systems”. End of 2011 he was bestowed the title “Associate Professor” in the field of research and teaching “Factory Automation”. He is working actively within technical committees of VDMA, GMA and AutomationML related to topics of engineering of production systems.

Sabine Wolny

Dipl.-Ing. Sabine Wolny is a PhD student at the Doctoral College Cyber-Physical Production Systems (CPPS) at TU Wien (http://dc-cpps.tuwien.ac.at). Her topic of interest is SysML-based modeling and execution of complex systems. Since 2013, she has been working in the Research Center of Building Physics and Sound Protection at TU Wien with a focus on project management and developing software solutions. For more information, please visit http://www.big.tuwien.ac.at/staff/swolny.

Manuel Wimmer

Ass.Prof. Mag. Dr. Manuel Wimmer is an assistant professor at the Business Informatics Group of TU Wien. He heads the Christian Doppler Laboratory for Model-Integrated Smart Production (CDL-MINT). His research interests comprise foundations of model-driven engineering techniques as well as their application in domains such as tool interoperability, legacy tool modernization, model versioning and evolution, and industrial engineering. For more information, please visit http://www.big.tuwien.ac.at/staff/mwimmer.

Dietmar Winkler

Dipl.-Ing. Dr. techn. Dietmar Winkler is a senior researcher at the Information and Software Engineering Group at TU Wien, Austria. He is currently working in the Christian Doppler Laboratory for “Security and Quality Improvement in the Production System Lifecycle” (CDL-SQI) at the faculty of Informatics at TU Wien. His research interests include software and systems engineering process and product improvement in multi-disciplinary engineering environments, quality management and quality assurance, as well as empirical evaluations in industrial settings. http://qse.ifs.tuwien.ac.at/~winkler.

Konstantin Kirchheim

Konstantin Kirchheim obtained his Bachelor degree in engineering and information sciences in 2017 at Otto-von-Guericke University and is currently studying within the related master program.

Ronald Rosendahl

Dipl.-Ing. Ronald Rosendahl attended the Otto-von-Guericke University Magdeburg and completed his diploma degree in computer visualistics. After working as a research assistant at IFAT, he is working as research assistant at IAF since 2012. His main field of interest are advanced engineering approaches and advanced (agent based) control systems.

Hessamedin Bayanifar

Dr.-Ing. M.Sc. Hessamedin Bayanifar completed his B.E. at Iran University of Science and Technology (IUST) in Industrial Engineering in 2011, and his MSc at University of Wollongong (UOW) in Manufacturing Engineering in 2014. In 2017 he completed his PhD at the OvGU Magdeburg on “Agent-based mechanism for smart distributed dependability and security control of Cyber-Physical Production Systems”.

Stefan Biffl

Ao. Univ.Prof. DI Mag. Dr.techn. Stefan Biffl was the head of the Christian Doppler Research Laboratory Software Engineering Integration for Flexible Automation Systems (CDL-Flex) at the faculty of Informatics at TU Wien. His research interests include product and process improvement for software-intensive systems and empirical evaluation in industrial environments.

Received: 2018-02-28

Accepted: 2018-07-06

Published Online: 2018-10-17

Published in Print: 2018-10-25

This work has been supported by the following research funds and organizations: Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, TU Wien research funds as well as the German Ministry for Economic Affairs and Energy within the PAICE program.

Citation Information: at - Automatisierungstechnik, Volume 66, Issue 10, Pages 819–833, ISSN (Online) 2196-677X, ISSN (Print) 0178-2312, DOI: https://doi.org/10.1515/auto-2018-0022.

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