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.Google Scholar
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.CrossrefWeb of ScienceGoogle Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Web of ScienceCrossrefGoogle Scholar
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.CrossrefGoogle Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
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.Web of ScienceGoogle Scholar
Patrick Könemann, Capturing the intention of model changes, in: Int. Conf. on Model Driven Engineering Languages and Systems, Springer, pp. 108–122, 2010.Google Scholar
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.Google Scholar
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.Web of ScienceGoogle Scholar
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.CrossrefGoogle Scholar
Philip Langer, Adaptable Model Versioning based on Model Transformation By Demonstration, Ph.D. thesis, Institut für Softwaretechnik und Interaktive Systeme, 2011.Google Scholar
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.Web of ScienceCrossrefGoogle Scholar
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.Google Scholar
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.Google Scholar
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.Google Scholar
About the article
Christopher Pietsch is scientific assistant in the Software Engineering and Database Systems Group at the University of Siegen, Germany. His main scientific interests are model-based system development, model co-evolution and delta-oriented model-based Software Product Line Engineering.
Prof. Dr. Udo Kelter holds the chair of Software Engineering and Database Systems at the University of Siegen, Germany. His main fields of research are model-based system development and version management.
Christopher Haubeck (born 1985) is a researcher in the Distributed Systems research unit in the department for informatics of the Hamburg University. His main scientific interests are software for distributed and cyber-physical systems, architectures for knowledge carrying software, coevolution of runtime artefacts and simulation.
Winfried Lamersdorf is a professor in the Informatics Department of Hamburg University and head of the Distributed Systems research unit. His main scientific interests are in the areas of system software for distributed systems, service-orientation, middleware, agent- and component-oriented, autonomous, self-organizing and mobile systems as well as related applications from e-business / e-services via business process management up to logistics and production automation.
Abhishek Chakraborty (born 1988) is currently working as a Research Associate with the Institute of Automation Technology at Helmut Schmidt University Hamburg. His main research interests are management of evolution in automated systems, behavior models and cyber-physical systems.
Prof. Dr.-Ing. Alexander Fay (born 1970) is Director of the Institute of Automation Technology at Helmut Schmidt University Hamburg. His main research interests are models, methods, and tools for the efficient engineering of distributed automation systems. Prof. Fay also heads the division “Engineering and operation” in the German association for Measurement and Automation (VDI-/VDE-GMA) and is member of the Scientific Advisory Board of the German Platform “Industrie 4.0”.
Published Online: 2018-10-17
Published in Print: 2018-10-25
Funding Source: Deutsche Forschungsgemeinschaft
Award identifier / Grant number: FA853/6-2
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.