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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


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2196-677X
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Volume 67, Issue 3

Issues

Application of a multi-disciplinary design approach in a mechatronic engineering toolchain

Anwendung eines multidisziplinären Designansatzes in einer mechatronischen Engineering Werkzeugkette

Huaxia Li
  • Corresponding author
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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/ Minjie Zou
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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/ Georg Hogrefe
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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/ Daria Ryashentseva
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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/ Michael Sollfrank
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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/ Gennadiy Koltun
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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/ Birgit Vogel-Heuser
  • 9184 Technical University of Munich, Institute of Automation and Information Systems, Boltzmannstr. 15, 85748 Garching near Munich, Germany
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Published Online: 2019-03-01 | DOI: https://doi.org/10.1515/auto-2018-0097

Abstract

Due to the increasing integration of different disciplines, the complexity in the development of mechatronic production systems is growing. To address this issue, a multi-disciplinary design approach has been proposed, which follows the model-based systems engineering (MBSE) architecture and integrates the interdisciplinary modeling approach SysML4Mechatronics. In this article, the applicability of this approach in the machine and plant manufacturing domain is demonstrated using five use cases. These use cases are derived from industry and are demonstrated in a lab-sized production plant. The results of the application show that the approach can completely fulfil the proposed industrial requirements, namely interdisciplinary modeling, comprehensibility of system modeling, reusability of the modeling components, coupling different engineering models and checking data consistency.

Zusammenfassung

Aufgrund der zunehmenden Integration verschiedener Disziplinen nimmt die Komplexität in der Entwicklung von mechatronischen Produktionssystemen zu. Um dieser Anforderung gerecht zu werden, wurde ein multidisziplinärer Designansatz vorgeschlagen, der auf der Architektur des Model-Based Systems Engineerings (MBSE) basiert und den interdisziplinären Modellierungsansatz SysML4Mechatronics integriert. In dem vorliegenden Beitrag wird die Anwendbarkeit dieses Ansatzes im Maschinen- und Anlagenbau anhand von fünf Anwendungsfällen vorgestellt. Diese Anwendungsfälle orientieren sich an einer industriellen Entwicklungsumgebung und werden auf den Demonstrator einer Produktionsanlage angewandt. Das Ergebnis der Umsetzung der Anwendungsfälle zeigt, dass der Entwicklungsprozess die vorgestellten, industriellen Anforderungen dieser Domäne vollständig erfüllt. Dazu gehören Anforderungen zur interdisziplinären Modellierung, zur Verständlichkeit der Systemmodellierung, zur Wiederverwendbarkeit der Modellierungskomponenten, zur Kopplung verschiedener Engineering Modelle und zum Inkonsistenzmanagement.

Keywords: multi-disciplinary design approach; model-based engineering; SysML4Mechatronics; mechatronic production system; machine and plant manufacturing

Schlagwörter: Multidisziplinärer Designansatz; Modelbasiertes Engineering; SysML4Mechatronics; Mechatronisches Produktionssystem; Maschinen- und Anlagenbau

References

  • 1.

    A. Strahilov and H. Hämmerle: Engineering Workflow and Software Tool Chains of Automated Production Systems. In: S. Biffl, A. Lüder, D. Gerhard (Eds.), Multi-Disciplinary Engineering for Cyber-Physical Production Systems, Springer, Cham, 2017, pp. 207–234.Google Scholar

  • 2.

    B. Vogel-Heuser, J. Fischer, S. Feldmann, S. Ulewicz and S. Rösch: Modularity and Architecture of PLC-based Software for Automated Production Systems: An analysis in industrial companies. In: Journal of Systems and Software, vol. 131, 2017, pp. 35–62.CrossrefGoogle Scholar

  • 3.

    International Council on Systems Engineering (INCOSE): Systems Engineering Vision 2020, Technical Report, Document No.: INCOSE-TP-2004-004-02, 2007.Google Scholar

  • 4.

    D. Winkler and S. Biffl: Improving Quality Assurance in Automation Systems Development Projects. In: M. Savsar (Ed.), Quality Assurance and Management, InTech, 2012, pp. 379–398.Google Scholar

  • 5.

    H. Li, M. Sollfrank, M. Zou, D. Ryashentseva and B. Vogel-Heuser: Consistent Automated Production Systems Modeling in a Multi-disciplinary Engineering Workflow. In: 44th Annual Conference of the IEEE Industrial Electronics Society (IECON), 2018, pp. 2971–2978.Google Scholar

  • 6.

    S. Biffl, R. Mordinyi and T. Moser: Anforderungsanalyse für das integrierte Engineering – Mechanismen und Bedarfe aus der Praxis. In: atp edition, vol. 54, no. 5, 2013, pp. 28–35.Google Scholar

  • 7.

    B. Vogel-Heuser and F. Ocker: Maintainability and evolvability of control software in machine and plant manufacturing – An industrial survey. In: Control Engineering Practice, vol. 80, 2018, pp. 157–173.CrossrefGoogle Scholar

  • 8.

    A. Lüder, N. Schmidt and M. John: Lossless exchange of automation project configuration data. In: IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), 2016, pp. 1–8.Google Scholar

  • 9.

    D. Winkler, F. Ekaputra and S. Biffl: AutomationML review support in multi-disciplinary engineering environments. In: IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), Berlin, 2016, pp. 1–9.Google Scholar

  • 10.

    S. Biffl, E. Maetzler, M. Wimmer, A. Lueder and N. Schmidt: Linking and versioning support for AutomationML: A model-driven engineering perspective. In: IEEE International Conference on Industrial Informatics (INDIN), 2015, pp. 499–506.Google Scholar

  • 11.

    S. Biffl, R. Mordinyi, H. Steininger and D. Winkler: Integrationsplattform für anlagenmodellorientiertes Engineering. In: B. Vogel-Heuser, T. Bauernhansl, M. ten Hompel (Eds.), Handbuch Industrie 4.0 Bd.2, Springer Vieweg, Berlin, Heidelberg, 2017, pp. 189–212.Google Scholar

  • 12.

    C. Hildebrandt, A. Scholz, A. Fay, T. Schröder, T. Hadlich, C. Diedrich, M. Dubovy, C. Eck and R. Wiegand: Semantic modeling for collaboration and cooperation of systems in the production domain. In: 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2017, pp. 1–8.Google Scholar

  • 13.

    A. Scholz, C. Hildebrandt and A. Fay: Functional modeling in production engineering workflows. In: IEEE 13th Conference on Automation Science and Engineering (CASE), 2017, pp. 695–700.Google Scholar

  • 14.

    S. Schröck, F. Zimmer, A. Fay and T. Jäger: Systematic reuse of interdisciplinary components supported by engineering relations. In: 15th IFAC Symposium on Information Control Problems in Manufacturing, vol. 48, no. 3, 2015, pp. 1545–1552.Google Scholar

  • 15.

    S. Vogel and S. Rudolph: Complex System Design with Design Languages: Method, Applications and Design Principles. In: XX International Conference “Complex systems: control and modeling problems” (CSCMP), 2018.Google Scholar

  • 16.

    K. Thramboulidis: The 3+1 SysML View-Model in Model Integrated Mechatronics. In: Journal of Software Engineering and Applications, vol. 3, no. 2, 2010, pp. 109–118.CrossrefGoogle Scholar

  • 17.

    K. Thramboulidis: Overcoming Mechatronic Design Challenges: The 3+1 SysML-View Model. In: The Computing Science and Technology International Journal, vol. 1, no. 1, 2013, pp. 6–14.Google Scholar

  • 18.

    A. A. Shah, A. A. Kerzhner, D. Schaefer and C. J. J. Paredis: Multi-View Modeling to Support Embedded Systems Engineering in SysML. In: G. Engels, C. Lewerentz, W. Schäfer, A. Schürr, B. Westfechtel (Eds.), Graph Transformations and Model-Driven Engineering. Lecture Notes in Computer Science, Springer, Berlin, Heidelberg, 2010, pp. 580–601.Google Scholar

  • 19.

    K. Kernschmidt, S. Feldmann and B. Vogel-Heuser: A model-based framework for increasing the interdisciplinary design of mechatronic production systems. In: Journal of Engineering Design, vol. 29, no. 11, 2018, pp. 617–643.CrossrefGoogle Scholar

  • 20.

    S. Feldmann, J. Fuchs and B. Vogel-Heuser: Modularity, Variant and Version Management in Plant Automation – Future Challenges and State of the Art. In: International Design Conference (DESIGN), 2012, pp. 1689–1698.Google Scholar

  • 21.

    G. Barbieri, G. Goldoni, R. Borsari and C. Fantuzzi: Modelling and Simulation for the Integrated Design of Mechatronic Systems. In: 2nd IFAC Conference on Embedded Systems, Computer Intelligence and Telematics CESCIT 2015, vol. 48, no. 10, 2015, pp. 75–80.Google Scholar

  • 22.

    G. Barbieri and C. Fantuzzi: Design of cyber-physical systems: Definition and metamodel for reusable resources. In: IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), 2016, pp. 1–9.Google Scholar

  • 23.

    R. Priego, A. Armentia, E. Estévez and M. Marcos: Modeling techniques as applied to generating tool-independent automation projects. In: at – Automatisierungstechnik, vol. 64, no. 4, 2016, pp. 325–340.Google Scholar

  • 24.

    H. Abid, P. Pernelle, D. Noterman, J. Campagne and C. B. Amar: SysML approach for the integration of mechatronics system within PLM systems. In: International Journal of Computer Integrated Manufacturing, vol. 28, no. 9, 2015, pp. 972–987.CrossrefGoogle Scholar

  • 25.

    M. Eigner, K. G. Faißt, T. Hollerith and F. Mogo Nem: A view-based modeling approach for representing multidisciplinary functions in PDM systems. In: Proceedings of DESIGN 2010, the 11th International Design Conference, 2010, pp. 1285–1294.Google Scholar

  • 26.

    M. Eigner, T. Dickopf, H. Apostolov, P. Schaefer, K. G. Faißt and A. Keßler: System Lifecycle Management: Initial Approach for a Sustainable Product Development Process Based on Methods of Model Based Systems Engineering. In: S. Fukuda, A. Bernard, B. Gurumoorthy, A. Bouras (Eds.), Product Lifecycle Management for a Global Market, PLM 2014, IFIP Advances in Information and Communication Technology, vol. 442, Springer, Berlin, Heidelberg, 2014, pp. 287–300.Google Scholar

  • 27.

    M. Grimm, R. Anderl and Y. Wang: Conceptual approach for multi-disciplinary cyber physical systems design and engineering. In: Proceedings of the Symposium on Tools & Methods of Competitive Engineering (TMCE), 2014, pp. 61–72.Google Scholar

  • 28.

    L. F. C. S. Durão, H. Eichhorn, R. Anderl, K. Schützer and E. de Senzi Zancul: Integrated Component Data Model Based on UML for Smart Components Lifecycle Management: A Conceptual Approach. In: A. Bouras, B. Eynard, S. Foufou, K. D. Thoben (Eds.), Product Lifecycle Management in the Era of Internet of Things, PLM 2015, IFIP Advances in Information and Communication Technology, vol. 467, Springer, Cham, 2016, pp. 13–22.Google Scholar

  • 29.

    F. Bellalouna: Integrationsplattform für eine interdisziplinäre Entwicklung mechatronischer Produkte. PhD Thesis, Ruhr University Bochum, Germany, 2009.Google Scholar

  • 30.

    M. Abramovici, Y. Aidi and H. B. Dang: Knowledge-Based Lifecycle Management Approach for Product Service Systems (PSS). In: A. Bernard, L. Rivest, D. Dutta (Eds.), Product Lifecycle Management for Society, PLM 2013, IFIP Advances in Information and Communication Technology, vol. 409, Springer, Berlin, Heidelberg, 2013, pp. 239–248.Google Scholar

  • 31.

    M. Abramovici, J. C. Göbel and H. B. Dang: Semantic data management for the development and continuous reconfiguration of smart products and systems. In: CIRP Annals, vol. 65, no. 1, 2016, pp. 185–188.CrossrefGoogle Scholar

  • 32.

    R. Harrison, D. Vera and B. Ahmad: Engineering Methods and Tools for Cyber–Physical Automation Systems. In: Proceedings of the IEEE, vol. 104, no. 5, 2016, pp. 973–985.CrossrefGoogle Scholar

  • 33.

    S. Konstantinov, M. Ahmad, K. Ananthanarayan and R. Harrison: The Cyber-physical E-machine Manufacturing System: Virtual Engineering for Complete Lifecycle Support. In: Procedia CIRP, vol. 63, 2017, pp. 119–124.Google Scholar

  • 34.

    K. Stark, T. Goldschmidt, J. Doppelhamer, P. Bihani and D. Goltz: Cloud-based integration of robot engineering data using AutomationML. In: 14th IEEE International Conference on Automation Science and Engineering (CASE), 2018, pp. 645–648.Google Scholar

  • 35.

    O. Carlsson: Engineering of IoT Automation Systems. PhD Thesis, Luleå University of Technology, Luleå, 2017.Google Scholar

  • 36.

    A. Demuth, M. Riedl-Ehrenleitner, A. Nöhrer, P. Hehenberger, K. Zeman and A. Egyed: DesignSpace: an infrastructure for multi-user/multi-tool engineering. In: Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015, pp. 1486–1491.Google Scholar

  • 37.

    A. Demuth, M. Riedl-Ehrenleitner and A. Egyed: Efficient detection of inconsistencies in a multi-developer engineering environment. In: Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering (ASE), 2016, pp. 590–601.Google Scholar

  • 38.

    H. Giese, S. Hildebrandt and S. Neumann: Model Synchronization at Work: Keeping SysML and AUTOSAR Models Consistent. In: G. Engels, C. Lewerentz, W. Schäfer, A. Schürr, B. Westfechtel (Eds.), Graph Transformations and Model-Driven Engineering, Lecture Notes in Computer Science, vol. 5765, Springer, Berlin, Heidelberg, 2010, pp. 555–579.Google Scholar

  • 39.

    G. Hinkel, T. Goldschmidt, E. Burger and R. Reussner: Using internal domain-specific languages to inherit tool support and modularity for model transformations. In: Software & Systems Modeling, 2017, pp. 1–27.Google Scholar

  • 40.

    C. Krupitzer, F. M. Roth, C. Becker, M. Weckesser, M. Lochau and A. Schürr: FESAS IDE: An Integrated Development Environment for Autonomic Computing. In: IEEE International Conference on Autonomic Computing (ICAC), 2016, pp. 15–24.Google Scholar

  • 41.

    VDI 2206: Design Methodology for Mechatronic Systems. Ed. Verein Deutscher Ingenieure, 2004.

  • 42.

    G. Barbieri, P. Derler, D. M. Auslander, R. Borsari and C. Fantuzzi: Design of mechatronic systems through aspect and object-oriented modeling. In: at – Automatisierungstechnik, vol. 64, no. 3, 2016, pp. 244–252.Google Scholar

  • 43.

    A. Lüder, N. Schmidt and R. Drath: Standardized Information Exchange Within Production System Engineering. In: S. Biffl, A. Lüder, D. Gerhard (Eds.), Multi-Disciplinary Engineering for Cyber-Physical Production Systems, Springer, 2017, pp. 235–257.Google Scholar

  • 44.

    M. E. Witte, C. Diedrich and H. Figalist: Model-based development in automation. In: at – Automatisierungstechnik, vol. 66, no. 5, 2018, pp. 360–371.CrossrefGoogle Scholar

  • 45.

    L. Berardinelli, S. Biffl, A. Lüder, E. Mätzler, T. Mayerhofer, M. Wimmer and S. Wolny: Cross-Disciplinary Engineering with AutomationML and SysML. In: at – Automatisierungstechnik, vol. 64, no. 4, 2016, pp. 253–269.Google Scholar

  • 46.

    C. Legat, J. Folmer and B. Vogel-Heuser: Evolution in Industrial Plant Automation: A Case Study. In: 39th Annual Conference of the IEEE Industrial Electronics Society (IECON), 2013, pp. 4386–4391.Google Scholar

  • 47.

    S. Feldmann, K. Kernschmidt and B. Vogel-Heuser: Combining a SysML-based modeling approach and semantic technologies for analyzing change influences in manufacturing plant models. In: 47th CIRP Conference on Manufacturing Systems (CMS), vol. 17, 2014, pp. 451–456.Google Scholar

  • 48.

    R. Drath, A. Luder, J. Peschke and L. Hundt: AutomationML – the glue for seamless automation engineering. In: 2008 IEEE International Conference on Emerging Technologies and Factory Automation, 2008, pp. 616–623.Google Scholar

  • 49.

    M. Wimmer and A. Mazak: From AutomationML to AutomationQL: A By-Example Query Language for CPPS Engineering Models. In: 14th IEEE International Conference on Automation Science and Engineering (CASE), 2018, pp. 1394–1399.Google Scholar

  • 50.

    M. Zou, B. Lu and B. Vogel-Heuser: Resolving Inconsistencies Optimally in the Model-Based Development of Production Systems. In: 14th IEEE International Conference on Automation Science and Engineering (CASE), 2018, pp. 1064–1070.Google Scholar

  • 51.

    H. Li, B. Vogel-Heuser and A. Gallasch: Kopplung des mechanischen Konstruktionsmodells in einem SysML4Mechatronics-Anlagenmodell zur Verbesserung des interdisziplinären Engineerings. In: 15. Fachtagung EKA – Entwurf komplexer Automatisierungssysteme (EKA), 2018.Google Scholar

  • 52.

    S. Thongnuch, A. Fay and R. Drath: Semi-automatic generation of a virtual representation of a production cell. In: at – Automatisierungstechnik, vol. 66, no. 5, 2018, pp. 372–384.CrossrefGoogle Scholar

  • 53.

    A. Kather and T. Voigt: Weihenstephaner Standards für die Betriebsdatenerfassung bei Getränkeabfüllanlagen, 2000.Google Scholar

About the article

Huaxia Li

Huaxia Li, M. Sc., graduated in mechanical engineering from the Technical University of Munich (TUM) in 2016. She is a research assistant at the Institute of Automation and Information Systems at TUM and a member of the Collaborative Research Centre SFB 768. Her main research interests are the model-based, cross-disciplinary development of mechatronic systems.

Minjie Zou

Minjie Zou, M. Sc., graduated in mechanical engineering from the Technical University of Munich (TUM) in 2016. She is a research assistant at the Institute of Automation and Information Systems at TUM and a member of the Collaborative Research Centre SFB 768. Her research interests include applying knowledge-based systems to verify and optimize the interdisciplinary development of automation engineering projects.

Georg Hogrefe

Georg Hogrefe, M. Sc. studied mechanical engineering with focus on automation and information systems at the Technical University of Munich (TUM). He graduated as Master of Science in 2018. During his master’s thesis he did research on tools for the industrial integration of Model-based Systems Engineering (MBSE) in plant engineering.

Daria Ryashentseva

Dr.-Ing. Daria Ryashentseva graduated in Automation of technological processes and production from the Southern Federal University, Russian Federation in 2010. She completed her PhD at the Otto von Guericke University, Magdeburg in 2016. She is a Postdoc at the Institute of Automation and Information Systems at TUM and manages coordination office of the Collaborative Research Center SFB 768. Her research interests include model-based design as well as distributed and intelligent control systems.

Michael Sollfrank

Michael Sollfrank, M. Sc., graduated in mechanical engineering from the Technical University of Munich (TUM) in 2016. He is a research assist ant at the Institute of Automation and Information Systems at TUM and a member of the Collaborative Research Centre SFB 768. His current research interests include the model-based engineering especially model-tool coupling. Other research interests are related to industrial communication.

Gennadiy Koltun

Gennadiy Koltun, Dipl.-Ing., graduated in electrical engineering from the Technical University of Dresden (TUD) in 2016. He is a research assistant at the Institute of Automation and Information Systems at TUM and a member of the Collaborative Research Centre SFB 768. His main research interests are systems engineering and model of distributed and reliable embedded systems.

Birgit Vogel-Heuser

Prof. Dr.-Ing Birgit Vogel-Heuser graduated in electrical engineering and received the Ph. D. in mechanical engineering from the RWTH Aachen in 1991. She worked for nearly ten years in industrial automation in the machine and plant manufacturing industry. She is the head of the Institute of Automation and Information Systems at TUM and the Collaborative Research Center SFB 768. Her research work is focused on system and software development, especially the modeling of distributed, intelligent and embedded systems.


Received: 2018-07-31

Accepted: 2018-12-21

Published Online: 2019-03-01

Published in Print: 2019-03-26


Citation Information: at - Automatisierungstechnik, Volume 67, Issue 3, Pages 246–269, ISSN (Online) 2196-677X, ISSN (Print) 0178-2312, DOI: https://doi.org/10.1515/auto-2018-0097.

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