Abstract
In the parallel engineering of large and long-running automation systems, such as Production Systems Engineering (PSE) projects, engineering teams with different backgrounds work in a so-called Round-Trip Engineering (RTE) process to iteratively enrich and refine their engineering artifacts, and need to exchange data efficiently to prevent the divergence of local engineering models. Unfortunately, the heterogeneity of local engineering artifacts and data, coming from several engineering disciplines, makes it hard to integrate the discipline-specific views on the data for efficient synchronization.
In this chapter, we introduce the approach of Engineering Data Logistics (EDaL) to support RTE requirements and enable the efficient integration and systematic exchange of engineering data in a PSE project. We propose the concept of EDaL, which analyzes efficient Engineering Data Exchange (EDEx) flows from data providers to a consumer derived from data exchange use cases. Requirements for EDEx flows are presented, for example, the definition and semantic mapping of engineering data elements for exchange. We discuss main requirements for and design elements of an EDaL information system for automating EDaL process capabilities. We evaluate the benefit and cost of the EDEx process and concepts in a feasibility case study with requirements and data from real-world use cases at a large PSE company in comparison to a traditional manual point-to-point engineering data exchange. Results from the feasibility study indicate that the EDEx process flows may be more effective than the traditional point-to-point engineering artifact exchange and a good foundation to EDaL for more agile engineering.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Andersen, A. L., ElMaraghy, H., ElMaraghy, W., Brunoe, T. D., & Nielsen, K. (2018). A participatory systems design methodology for changeable manufacturing systems. International Journal of Production Research, 56(8), 2769–2787.
Biffl, S., Winkler, D., Mordinyi, R., Scheiber, S., & Holl, G. (2014a, September). Efficient monitoring of multi-disciplinary engineering constraints with semantic data integration in the multi-model dashboard process. In Emerging technology and factory automation (ETFA). IEEE.
Biffl, S., Lüder, A., Schmidt, N., & Winkler, D. (2014b, October). Early and efficient quality assurance of risky technical parameters in a mechatronic design process. In Industrial electronics society, IECON 2014-40th annual conference of the IEEE (pp. 2544–2550). IEEE.
Biffl, S., Gerhard, D., & Lüder, A. (2017). Introduction to the multi-disciplinary engineering for cyber-physical production systems. In Multi-disciplinary engineering for cyber-physical production systems (pp. 1–24). Cham: Springer.
Biffl, S., Eckhart, M., Lüder, A., Müller, T., Rinker, F., & Winkler, D. (2018). Data interface for coil car simulation (case study) part I, Technical Report, CDL-SQI-M2-TR02, TU Wien.
Biffl, S., Eckhart, M., Lüder, A., Müller, T., Rinker, F., & Winkler, D. (2019a). Data interface for coil car simulation (case study) part II - Detailed data and process models, Technical Report, CDL-SQI-M2-TR03, TU Wien.
Biffl, S., Lüder, A., Rinker, F., Waltersdorfer, L., & Winkler, D. (2019b). Introducing engineering data logistics for production systems engineering, Technical Report, CDL-SQI-2018-10, TU Wien. October, 2018. http://qse.ifs.tuwien.ac.at/wp-content/uploads/CDL-SQI-2018-10.pdf.
Biffl, S., Lüder, A., Rinker, F., Waltersdorfer, L., & Winkler, D. (2019c). Efficient engineering data exchange in multi-disciplinary systems engineering. In Proceeding of international conference on advanced information systems engineering (pp. 17–31). Cham: Springer.
Brambilla, M., Cabot, J., & Wimmer, M. (2017). Model-driven software engineering in practice. In Synthesis lectures on software engineering (Vol. 3, 2nd ed., pp. 1–207). San Rafael, CA: Morgan & Claypool.
Broy, M., Feilkas, M., Herrmannsdoerfer, M., Merenda, S., & Ratiu, D. (2010). Seamless model-based development: From isolated tools to integrated model engineering environments. Proceedings of the IEEE, 98(4), 526–545.
Calà, A., Lüder, A., Cachada, A., Pires, F., Barbosa, J., Leitão, P., & Gepp, M. (2017, July). Migration from traditional towards cyber-physical production systems. In Industrial informatics (INDIN), 2017 IEEE 15th international conference (pp. 1147–1152). IEEE.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, MIT.
Diedrich, C., Lüder, A., & Hundt, L. (2011). Bedeutung der Interoperabilität bei Entwurf und Nutzung von automatisierten Produktionssystemen. at-Automatisierungstechnik Methoden und Anwendungen der Steuerungs-, Regelungs- und Informationstechnik, 59(7), 426–438.
Drath, R. (Ed.). (2009). Datenaustausch in der Anlagenplanung mit AutomationML: Integration von CAEX, PLCopen XML und COLLADA. Berlin: Springer.
Drath, R., Fay, A., & Barth, M. (2011). Interoperabilität von Engineering-Werkzeugen. at–Automatisierungstechnik, 59(7), 451–460.
Gould, P. (1997). What is agility? Manufacturing Engineer, 76(1), 28–31.
Grose, T. J., & Doney, G. C. (2002). PhD. Stephan A. Brodsky. Mastering XMI. Java programming with XMI, XML, and UML. Wiley.
Hell, K. (2018). Methoden der projektübergreifenden Wiederverwendung im Anlagenentwurf: Konzeptionierung und Realisierung in der Automobilindustrie, Dissertation, Fakultät Maschinenbau, Otto-v.-Guericke Universität Magdeburg.
Hohpe, G., & Woolf, B. (2003). Enterprise integration patterns: Designing, building, and deploying messaging solutions. Boston, MA: Addison-Wesley.
Holl, G., Thaller, D., Grünbacher, P., & Elsner, C. (2012). Managing emerging configuration dependencies in multi product lines. In Proceedings of the Sixth International Workshop on Variability Modeling of Software-Intensive Systems (pp. 3–10). ACM.
IEC 62714. (2018). Engineering data exchange format for use in industrial automation systems engineering - automation markup language, 4 Parts 1, IEC, 2014–2018.
Jackson, M., & Johansson, C. (2003). An agility analysis from a production system perspective. Integrated Manufacturing Systems, 14(6), 482–488.
Jimenez-Ramirez, A., Barba, I., Reichert, M., Weber, B., & Del Valle, C. (2018, June). Clinical processes-the killer application for constraint-based process interactions? In International conference on advanced information systems engineering (pp. 374–390). Berlin: Springer.
Kovalenko, O., & Euzenat, J. (2016). Semantic matching of engineering data structures. In S. Biffl & M. Sabou (Eds.), Semantic web for intelligent engineering applications. Berlin: Springer.
Lüder, A., & Schmidt, N. (2017). AutomationML in a nutshell. In Handbuch Industrie 4.0 Bd. 2 (pp. 213–258). Berlin: Springer.
Lüder, A., Pauly, J.-L., Kirchheim, K., Rinker, F., & Biffl, S. (2018a). Migration to AutomationML based tool chains – Incrementally overcoming engineering network challenges. In Proceeding of 5th AutomationML user conference, Göteborg, 24/25.10.2018; AML Association. https://www.automationml.org/o.red/uploads/dateien/1548668540-17_Lueder_Migration-ToolChains_Paper.pdf.
Lüder, A., Pauly, J.-L., Rosendahl, R., Biffl, S., & Rinker, F. (2018b). Support for engineering chain migration towards multi-disciplinary engineering chains. In 2018 14th IEEE international conference on automation science and engineering (CASE 2018) (pp. 671–674). Germany, August 2018, IEEE.
Medvidovic, N., Egyed, A., & Rosenblum, D. S. (1999, September). Round-trip software engineering using UML: From architecture to design and back. In Proceeding of the second international workshop on object-oriented reengineering (WOOR’99) (pp. 1–8). Cham: Springer.
OMG. (2011). Business process model notation (BPMN) version 2.0. OMG specification (pp. 22–31). Object Management Group.
Putze, S., Porzel, R., Savino, G. L., & Malaka, R. (2018, June). A manageable model for experimental research data: An empirical study in the materials sciences. In International conference on advanced information systems engineering (pp. 424–439). Cham: Springer.
Rosemann, M., & vom Brocke, J. (2015). The six core elements of business process management. In Handbook on business process management (Vol. 1, pp. 105–122). Berlin: Springer.
Runeson, P., & Höst, M. (2009). Guidelines for conducting and reporting case study research in software engineering. Empirical Software Engineering, 14(2), 131–164.
Sabou, M., Ekaputra, F. J., & Biffl, S. (2017). Semantic web technologies for data integration in multi-disciplinary engineering. In S. Biffl, A. Lüder, & D. Gerhard (Eds.), Multi-disciplinary engineering of cyber-physical production systems. Cham: Springer.
Schäffler, T., Foehr, M., Lüder, A., & Supke, K. (2013, May). Engineering process evaluation: Evaluation of the impact of internationalisation decisions on the efficiency and quality of engineering processes. In 2013 IEEE International Symposium on Industrial Electronics (pp. 1–6). IEEE.
VDI. (2012–2017). VDI-Richtlinie: VDI/VDE 3690 XML in der automation. Berlin: Beuth.
Vogel-Heuser, B., Bauernhansl, T., & ten Hompel, M. (Ed.). (2017). Handbuch Industrie 4.0, Bände 1-4, VDI Springer.
Wieringa, R. (2014). Design science methodology for information systems and software engineering. Berlin: Springer.
Winkler, D., Sabou, M., & Biffl, S. (2017). Improving quality assurance in multi-disciplinary engineering environments with semantic technologies. In L. D. Kounis (Ed.), Quality control and assurance – An ancient Greek term ReMastered. Book Chapter 8 (pp. 177–200). London: INTEC Publishing.
Xu, X. (2012). From cloud computing to cloud manufacturing. Robotics and Computer-Integrated Manufacturing, 28(1), 75–86.
Acknowledgments
The financial support by the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs, and the National Foundation for Research, Technology and Development is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Biffl, S., Lüder, A., Rinker, F., Waltersdorfer, L., Winkler, D. (2019). Engineering Data Logistics for Agile Automation Systems Engineering. In: Biffl, S., Eckhart, M., Lüder, A., Weippl, E. (eds) Security and Quality in Cyber-Physical Systems Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-25312-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-25312-7_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-25311-0
Online ISBN: 978-3-030-25312-7
eBook Packages: Computer ScienceComputer Science (R0)