Abstract
During systems design, systems engineers would like to reason about systems feasibility as early in the process as possible. In this chapter, we present a model-based systems engineering (MBSE) method to support design decisions early in the process of systems development by quantitative information about important system qualities. We focus on productivity and propose a method based on system workflows that provide customer value. We annotate the workflows with quantitative information and resources being used and define a formal semantics for these workflows to enable analysis by means of simulation. The approach reuses constructs of the MBSE method Arcadia and is supported by prototype tooling in the form of an add-on of the tool Capella. We visualize simulation results using Gantt charts, with several viewing possibilities and critical path analysis. Finally, the add-on includes design space exploration functionality, which supports specification of parameter ranges and automatic simulation of all combinations. This integrates early design space exploration with MBSE.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
C. Singam, Model-based systems engineering (MBSE) (2022), https://www.sebokwiki.org/wiki/Model-Based_Systems_Engineering_(MBSE)
J.A. Estefan, T. Weilkiens, MBSE methodologies, in Handbook of Model-Based Systems Engineering, (Springer, 2022), pp. 1–40
J.A. Estefan, Survey of model-based systems engineering (MBSE) methodologies, in INCOSE MBSE Initiative (2008)
J. Ma, G. Wang, J. Lu, H. Vangheluwe, D. Kiritsis, Y. Yan, Systematic literature review of MBSE tool-chains. Appl. Sci. 12, 3431 (2022)
T. Weilkiens, MBSE tools (2022), https://mbse4u.com/sysml-tools/
Critical To Quality (CTQ) (2022), https://www.isixsigma.com/dictionary/critical-to-quality-ctq/
P.F. Smith, S.M. Prabhu, J. Friedman, Best practices for establishing a model-based design culture. SAE Technical Paper (2007)
Thermo Fisher Scientific, Electron microscopy (2022), https://www.thermofisher.com/nl/en/home/electron-microscopy.html
Electron microscope (2023), https://en.wikipedia.org/wiki/Electron_microscope
Electron Microscopy Learning Center (2023), https://www.thermofisher.com/nl/en/home/electron-microscopy/learning-center.html
Arcadia/Capella (2022), https://www.eclipse.org/capella/arcadia.html
N. Roos, Thermo Fisher Scientific develops an appetite for modeling (2022), https://bits-chips.nl/artikel/thermo-fisher-scientific-develops-an-appetite-for-modeling/
Property Values Management Tools (PVMT) (2022), https://www.eclipse.org/capella/addons.html
POOSL (2022), https://www.poosl.org/
Eclipse TRACE4CPS (2022), https://projects.eclipse.org/projects/technology.trace4cps
Design space exploration of workflows in Capella (2022), https://github.com/TNO/capella-workflow-dse
M.S. Erden, H. Komoto, T.J. van Beek, V. D’Amelio, E. Echavarria, T. Tomiyama, A review of function modeling: approaches and applications. Artif. Intell. Eng. Des. Anal. Manuf. 22, 147–169 (2008)
K.E. Bemmami, P. David, State-of-practice survey in industry on the deployment of simulation in systems engineering. IFAC-PapersOnLine 54(1), 1132–1137 (2021)
OBEO, What if you could simulate your Capella model? (2021), https://news.obeosoft.com/en/post/what-if-you-could-simulate-your-capella-model
L. Rioux, R. Henia, N. Sordon, Using model-checking for timing verification in industrial system design, in 2017 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), (IEEE, 2017), pp. 377–378
L. Batista, O. Hammami, Capella based system engineering modelling and multi-objective optimization of avionics systems, in 2016 IEEE International Symposium on Systems Engineering (ISSE), (IEEE, 2016), pp. 1–8
B. Eisenbart, K. Gericke, L. Blessing, Taking a look at the utilisation of function models in interdisciplinary design: insights from ten engineering companies. Res. Eng. Des. 28, 299–331 (2017)
J.E. Long, Relationships between common graphical representations in systems engineering. Insight 21(1), 8–11 (2018)
B. van der Sanden, Y. Blankenstein, R. Schiffelers, J. Voeten, LSAT: specification and analysis of product logistics in flexible manufacturing systems, in 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), (IEEE, 2021), pp. 1–8
BPMN Specification (2022), https://www.bpmn.org/
K. Traganos, D. Spijkers, P. Grefen, I. Vanderfeesten, Dynamic process synchronization using BPMN 2.0 to support buffering and (un)bundling in manufacturing, in Business Process Management Forum. BPM 2020, Lecture Notes in Business Information Processing, ed. by D. Fahland, C. Ghidini, J. Becker, M. Dumas, vol. 392, (Springer, 2020), pp. 18–34
J. Wang, Deterministic timed petri nets, in Timed Petri Nets, The Kluwer International Series on Discrete Event Dynamic Systems, vol. 9, (Springer, 1998), pp. 37–61
K. Salimifard, M. Wright, Petri net-based modelling of workflow systems: an overview. Eur. J. Oper. Res. 134(3), 664–676 (2001)
M. Herget, F.S. Saadatmand, M. Bor, I. González Alonso, T. Stefanov, B. Akesson, A.D. Pimentel, Design space exploration for distributed cyber-physical systems: state-of-the-art, challenges, and directions, in 2022 25th Euromicro Conference on Digital System Design (DSD), (IEEE, 2022), pp. 632–640
K. Miranda, W. Girard-Dias, M. Attias, W. de Souza, I. Ramos, Three dimensional reconstruction by electron microscopy in the life sciences: an introduction for cell and tissue biologists. Mol. Reprod. Dev. 82(7–8), 530–547 (2015)
P. Roques, Systems Architecture Modeling with the Arcadia Method – A Practical Guide to Capella (ISTE Press – Elsevier, 2018)
F. Pommereau, Nets-in-nets with SNAKES, in Fifth International Workshop on Modelling of Objects, Components, and Agents (MOCA’09) (2009), pp. 107–126
SNAKES, the net algebra kit for editors and simulators (2022), https://snakes.ibisc.univ-evry.fr/
J.P. López-Grao, J. Merseguer, J. Campos, From UML activity diagrams to Stochastic Petri nets: application to software performance engineering, in WOSP ’04: Proceedings of the 4th International Workshop on Software and Performance, (ACM, 2004), pp. 25–36
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Hooman, J., Kanters, K., Vasenev, A., Verriet, J. (2024). MBSE-Based Design Space Exploration for Productivity Improvement Using Workflow Models. In: Verma, D., Madni, A.M., Hoffenson, S., Xiao, L. (eds) The Proceedings of the 2023 Conference on Systems Engineering Research. CSER 2023. Conference on Systems Engineering Research Series. Springer, Cham. https://doi.org/10.1007/978-3-031-49179-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-031-49179-5_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-49178-8
Online ISBN: 978-3-031-49179-5
eBook Packages: EngineeringEngineering (R0)