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Using model differencing to reason about observable behavior changes of manufacturing systems

Nutzung von Modelldifferenzen zum Schließen auf beobachtbare Verhaltensänderungen von Fertigungssystemen
Christopher Pietsch, Udo Kelter, Christopher Haubeck, Winfried Lamersdorf, Abhishek Chakraborty and Alexander Fay


Understanding changes in a manufacturing system is of utmost importance to effectively manage its evolution. This article proposes a pattern-based approach for capturing and describing behavioral changes by integrating recent advantages in the fields of system monitoring and model differencing. Observed changes are described as lifted model differences between two model versions. This helps in explaining observable evolution with a change-first approach.


Durch den fortwährenden Evolutionsprozess unterliegen Produktionssysteme einem stetigen Wandel ihres Verhaltens. Um Evolution systematisch zu verstehen, müssen diese Änderungen erfasst werden. Dazu wird ein musterbasierter Ansatz zur Erkennung von Verhaltensänderungen vorgestellt, der Evolution durch beobachtbare und semantisch angereicherte Änderungen beschreibt und als zentrales Artefakt der Evolution etabliert.

Funding source: Deutsche Forschungsgemeinschaft

Award Identifier / Grant number: FA853/6-2

Funding statement: This work was partially supported by the DFG (German Research Foundation) under the Priority Programme SPP1593: Design for Future – Managed Software Evolution, under grant no. FA853/6-2.


1. Luca Berardinelli, Stefan Biffl, Emanuel Maetzler, Tanja Mayerhofer and Manuel Wimmer, Model-based co-evolution of production systems and their libraries with AutomationML, in: Conf. on Emerging Technologies and Factory Automation.Search in Google Scholar

2. Valentina Boschian, Mariagrazia Dotoli, Maria Pia Fanti, Giorgio Iacobellis and Walter Ukovich, A metamodeling approach to the management of intermodal transportation networks, Transactions on Automation Science and Engineering 8 (2011), 457–469.10.1109/TASE.2010.2090870Search in Google Scholar

3. Petra Brosch, Philip Langer, Martina Seidl, Konrad Wieland, Manuel Wimmer andet al., An example is worth a thousand words: Composite operation modeling by-example, in: Int. Conf. on Model Driven Engineering Languages and Systems, Springer, pp. 271–285, 2009.Search in Google Scholar

4. Abhishek Chakraborty, Christopher Haubeck, Alexander Fay and Winfried Lamersdorf, Signal-based Context Comparative Analysis for Identification of Similar Manufacturing Modules, in: 16th Symposium on Information Control Problems in Manufacturing, 2018.Search in Google Scholar

5. Antonio Cicchetti, Davide Di Ruscio and Alfonso Pierantonio, Model patches in model-driven engineering, in: Int. Conf. on Model Driven Engineering Languages and Systems, Springer, pp. 190–204, 2009.Search in Google Scholar

6. E. Estévez, Marga Marcos, Arndt Lüder and Lorenz Hundt, PLCopen for achieving interoperability between development phases, in: Conf. on Emerging Technologies and Factory Automation, IEEE, pp. 1–8, 2010.Search in Google Scholar

7. Liqing Fan, Bhat Nikhil Jagdish, A Senthil Kumar, Subramanian Anbuselvan and Shung-Hwee Bok, Collaborative fixture design and analysis using service oriented architecture, transactions on automation science and engineering 7 (2010), 617–629.10.1109/TASE.2009.2038069Search in Google Scholar

8. Stefan Feldmann, Konstantin Kernschmidt and Birgit Vogel-Heuser, Combining a SysML-based modeling approach and semantic technologies for analyzing change influences in manufacturing plant models, Procedia CIRP 17 (2014), 451–456.10.1016/j.procir.2014.01.140Search in Google Scholar

9. Timo Kehrer, Udo Kelter, Pit Pietsch and Maik Schmidt, Adaptability of model comparison tools, in: Procc of the 27th Int. Conf. on Automated Software Engineering, ACM, pp. 306–309, 2012.Search in Google Scholar

10. Timo Kehrer, Udo Kelter and Gabriele Taentzer, A rule-based approach to the semantic lifting of model differences in the context of model versioning, in: Proc. of the 26th Int. Conf. on Automated Software Engineering, IEEE, pp. 163–172, 2011.Search in Google Scholar

11. Timo Kehrer, Udo Kelter and Gabriele Taentzer, Consistency-preserving edit scripts in model versioning, in: Int. Conf. on Automated Software Engineering, IEEE, pp. 191–201, 2013.Search in Google Scholar

12. Timo Kehrer, Udo Kelter and Gabriele Taentzer, Propagation of software model changes in the context of industrial plant automation, at-Automatisierungstechnik 62 (2014), 803–814.Search in Google Scholar

13. Patrick Könemann, Capturing the intention of model changes, in: Int. Conf. on Model Driven Engineering Languages and Systems, Springer, pp. 108–122, 2010.Search in Google Scholar

14. J. Ladiges, A. Fülber, E. Arroyo, A. Fay, C. Haubeck and W. Lamersdorf, Learning material flow models for manufacturing plants from data traces, in: 2015 IEEE 13th International Conference on Industrial Informatics (INDIN), IEEE, pp. 294–301, 2015.Search in Google Scholar

15. Jan Ladiges, Christopher Haubeck, Alexander Fay and Winfried Lamersdorf, Evolution management of production facilities by semi-automated requirement verification, at-Automatisierungstechnik 62 (2014), 781–793.Search in Google Scholar

16. Jan Ladiges, Christopher Haubeck, Alexander Fay and Winfried Lamersdorf, Learning behaviour models of discrete event production systems from observing input/output signals, IFAC-PapersOnLine 48 (2015), 1565–1572.10.1016/j.ifacol.2015.06.309Search in Google Scholar

17. Philip Langer, Adaptable Model Versioning based on Model Transformation By Demonstration, Ph.D. thesis, Institut für Softwaretechnik und Interaktive Systeme, 2011.Search in Google Scholar

18. Daniel Regulin, Thomas Aicher and Birgit Vogel-Heuser, Improving transferability between different engineering stages in the development of automated material flow modules, Transactions on Automation Science and Engineering 13 (2016), 1422–1432.10.1109/TASE.2016.2576022Search in Google Scholar

19. Miriam Schleipen, Arndt Lüder, Olaf Sauer, Holger Flatt and Jürgen Jasperneite, Requirements and concept for plug-and-work, at-Automatisierungstechnik 63 (2015), 801–820.Search in Google Scholar

20. Martin Strube, Stefan Runde, Helmut Figalist and Alexander Fay, Risk minimization in modernization projects of plant automation—a knowledge-based approach by means of semantic web technologies, in: Conf. on Emerging Technologies & Factory Automation, IEEE, pp. 1–8, 2011.Search in Google Scholar

21. Birgit Vogel-Heuser, Stefan Feldmann, Jens Folmer, Jan Ladiges, Alexander Fay andet al., Selected challenges of software evolution for automated production systems, in: Int. Conf. on Industrial Informatics, IEEE, pp. 314–321, 2015.Search in Google Scholar

22. Birgit Vogel-Heuser, Christoph Legat, Jens Folmer and Stefan Feldmann, Researching evolution in industrial plant automation: Scenarios and documentation of the pick and place unit, Institute of Automation and Information Systems, Technische Universität München, Report, 2014.Search in Google Scholar

23. Valeriy Vyatkin, Software engineering in industrial automation: State-of-the-art review, Transactions on Industrial Informatics 9 (2013), 1234–1249.10.1109/TII.2013.2258165Search in Google Scholar

Received: 2018-04-08
Accepted: 2018-07-30
Published Online: 2018-10-17
Published in Print: 2018-10-25

© 2018 Walter de Gruyter GmbH, Berlin/Boston