Model Based Systems Engineering Concepts

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Systems Engineering for Automotive Powertrain Development

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Abstract

Increases in system complexity and development effort along with the industrial push to be cost-efficient and reduce time to market have created an urgency for new approaches to systems engineering. One part of the systems engineering (SE) approach is model-based systems engineering. Model-based systems engineering (MBSE) supports systems engineering activities such as system requirements definition, system architecture definition, as well as activities in later phases by moving from a document-based to a model-based engineering approach. The main focus of MBSE is to generate system models beside specific models which then act as an interdisciplinary communication platform to provide information such as system-related statements. This chapter provides an overview of MBSE and its interaction with model-based development (MBD) approaches.

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References

  • AVL CRUISE M (2019) Multi-disciplinary system simulation. Online accessed 14 Mar 2019. https://www.avl.com/web/guest/-/avl-cruise-2

  • AVL VSM (2019) Vehicle dynamic simulation. Online accessed 14 Mar 2019. https://www.avl.com/web/guest/-/avl-vsm-4-

  • Blanchard BS, Fabrycky WJ (2013) Systems engineering and analysis, 5th edn. Pearson Education Limited, London; ISBN: 978-1-292-03839-1

    Google Scholar 

  • Boschert S, Rosen R (2016) In: Hehenberger P, Bradley D (eds) Digital twin – the simulation aspect; mechatronic futures. Springer; ISBN: 978-3-319-32154-7

    Google Scholar 

  • Box GEP, Draper NR (1987) Empirical model-building and response surfaces, 1st edn. Wiley. series-ed: Balding, David, J., et al.; Wiley series in probability and statistics, New York; ISBN: 978-0471810339

    Google Scholar 

  • Cambridge (2019a) Cambridge dictionary. Online accessed 4 June 2019. https://dictionary.cambridge.org/de/worterbuch/englisch/formalize?q=formalized

  • Cambridge (2019b) Cambridge dictionary. Online accessed 4 Sept 2019. https://dictionary.cambridge.org/de/worterbuch/englisch/repository

  • Deloitte (2019) Grenzenlos vernetzt: Digital Twins – Smarte Digitalisierung durch IoT, Digitale Zwillinge und die Supra-Plattform. Online accessed 17 Sept 2019. https://www2.deloitte.com/de/de/pages/technology-media-and-telecommunications/articles/digital-twins.html

  • Department of Defense DoD (2011) Modeling and simulation (M&S). Glossary; Modeling and Simulation Coordination Office, Alexandria

    Google Scholar 

  • Dori D (2016) Model-based systems engineering with OPM and SysML, 1st edn. Springer, New York; ISBN: 978-1493932948

    Google Scholar 

  • Dvorak D (2013a) Model-centric engineering, part 1: an introduction to model-based systems engineering. NASA

    Google Scholar 

  • Dvorak D (2013b) Model-centric engineering, part 2: introduction to system modeling. NASA

    Google Scholar 

  • Eigner M, Gilz T, Zafirov R (2012) Proposal for functional product description as part of a PLM solution in interdisciplinary product development. In: International Design Conference, Dubrovnik, 21–24 May

    Google Scholar 

  • Eigner M, Roubanov D, Zafirov R (2014) Modellbasierte virutelle Produktentwicklung. Springer, Berlin/Heidelberg; ISBN: 978-3-662-43816-9

    Google Scholar 

  • Estefan JA (2008) Survey of model-based systems engineering (MBSE) methodologies. Jet Propulsion Laboratory. 23.05.2008; INCOSE MBSE Initiative, Pasadena

    Google Scholar 

  • Friedenthal S, Moore A, Steiner R (2011) A practical guide to SysML Morgan Kaufmann, 2nd edn, Waltham; ISBN: 978-0-12-385206-9

    Google Scholar 

  • Grieves M, Vickers J (2017) Digital twin: mitigating unpredictable, undesirable emergent behavior. In: Kahlen F-J, Flumerfelt S, Alves A (eds) Complex systems; transdisciplinary perspectives on complex systems. Springer, Cham; ISBN: 978-3-319-38756-7

    Google Scholar 

  • Haberfellner R, de Weck O, Fricke E, Vössner S (2015) Systems Engineering – Grundlagen und Anwendung, 13th edn. Orell Füssli, Zürich; ISBN: 978-3-280-04068-3

    Google Scholar 

  • Hick H, Bajzek M, Faustmann C (2019) Definition of a system model for model-based development. SN Applied Sciences. Online accessed 28 Aug 2019. https://springer.longhoe.net/article/10.1007%2Fs42452-019-1069-0

  • Honour EC (2004) Understanding the value of systems engineering. In INCOSE international symposium, 14.01.2007, Toulouse; 20–24.06. pp 1207–1222

    Google Scholar 

  • IBM Knowledge Center (2019) The harmony process. Online accessed 11 Sept 2019. https://www.ibm.com/support/knowledgecenter/SSB2MU_8.3.0/com.btc.tcatg.user.doc/topics/atgreqcov_SecSysControllerHarmony.html

  • INCOSE Systems Engineering Vision 2020, INCOSE (2007) Document no: INCOSE-TP-2004-004-02; Version: 2.03

    Google Scholar 

  • Kossiakoff A, Sweet WN, Seymour SJ, Biemer SM (2011) Systems engineering – principles and practice, 2nd edn. Wiley. series-ed: Sage, Andrew P. Wiley series in systems engineering and management, Hoboken; ISBN: 978-1118001028

    Google Scholar 

  • Kritzinger W, Karner M, Traar G, Henjes J, Sihn W (2018) Digital twin in manufacturing: a categorical literature review and classification. Elsevier

    Google Scholar 

  • Long D, Scott Z (2011) A primer for model-based systems engineering, 2nd edn; ISBN: 978-1-105-58810-5

    Google Scholar 

  • Lünnemann P, Wang WM, Lindow K (2019) Smart Industrial Products – Smarte Produkte und ihr Einfluss auf Geschäftsmodelle, Zusammenarbeit, Portfolios und Infrastrukturen. Fraunhorfer IPK, CONTACT Software. Online accessed 17 Sept 2019. https://www.ipk.fraunhofer.de/fileadmin/user_upload/IPK/publikationen/markt-_und_trendstudien/Studie_Smart_Industrial_Products.pdf

  • Madni AM, Madni CC, Lucero SD (2019) Leveraging digital twin technology in model-based systems engineering. Systems. Online accessed 6 Oct 2019. https://www.mdpi.com/2079-8954/7/1/7

  • Maier MM, Rechtin E (2009) The art of systems architecting, 3rd edn. Taylor & Francis Inc., Boca Raton; ISBN: 978-1420079135

    Google Scholar 

  • NASA (2019) Jet propulsion laboratory; technology mission data system – state analysis. Online accessed 11 Sept 2019. https://mds.jpl.nasa.gov/public/sa/

  • Paulweber M, Lebert K (2014) Powertrain instrumentation and test systems, 1st edn. Springer Nature, Wiesbaden; ISBN: 978-3-319-32133-2

    Google Scholar 

  • Polarsys (2019) Arcadia method. Online accessed 11 Sept 2019. https://www.polarsys.org/capella/arcadia.html

    Google Scholar 

  • Qi Q, Tao F (2018) Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison. IEEE; Online accessed 28 Aug 2019. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8258937

  • Schäuffele J, Zurawka T (2013) Automotive Software Engineering – Grundlagen, Prozesse, Methoden und Werkzeuge effizient einsetzen, 5th edn. Springer, Wiesbaden; ISBN: 978-3-8348-2469-1

    Google Scholar 

  • Stachowiak H (1973) Allgemeine Modelltheorie. Springer, Wien/New York; ISBN: 0-387-81106-0

    Google Scholar 

  • Stark R, Damerau T (2019) Digital twin; the international academy for production engineering. In: Chatti S, Tolio T (eds) CIRP encyclopedia of production engineering. Springer, Berlin/Heidelberg

    Google Scholar 

  • OMG (2017) OMG systems modeling language; Version 1.5; 05–2017

    Google Scholar 

  • VDI 2221 (1993) Methodik zum Entwickeln und Konstruieren technischer Systeme und Produkte. VDI

    Google Scholar 

  • Walden DD, Roedler GJ, Forsberg KJ, Hamelin RD, Shortell TM (2015) INCOSE systems engineering handbook – a guide for system life cycle processes and activities, 4th edn. Wiley, Hoboken; ISBN: 978-1118999400

    Google Scholar 

  • Weilkiens T (2008) Systems Engineering mit SysML/UML: Modellierung, Analyse, Design, 2nd edn. dpunkt, Heidelberg; ISBN: 978-3898645775

    Google Scholar 

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Correspondence to Matthias Bajzek .

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Bajzek, M., Fritz, J., Hick, H., Maletz, M., Faustmann, C., Stieglbauer, G. (2021). Model Based Systems Engineering Concepts. In: Hick, H., Küpper, K., Sorger, H. (eds) Systems Engineering for Automotive Powertrain Development. Powertrain. Springer, Cham. https://doi.org/10.1007/978-3-319-68847-3_8-2

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  • DOI: https://doi.org/10.1007/978-3-319-68847-3_8-2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68847-3

  • Online ISBN: 978-3-319-68847-3

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Model Based Systems Engineering Concepts
    Published:
    10 November 2020

    DOI: https://doi.org/10.1007/978-3-319-68847-3_8-2

  2. Original

    Model Based Systems Engineering Concepts
    Published:
    29 October 2020

    DOI: https://doi.org/10.1007/978-3-319-68847-3_8-1

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