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STUDY OF SYSTEM INTERFACES THROUGH THE NOTION OF COMPLEMENTARITY

Published online by Cambridge University Press:  27 July 2021

Yana Brovar*
Affiliation:
Skolkovo Institute of Science and Technology (Skoltech)
Yaroslav Menshenin
Affiliation:
Skolkovo Institute of Science and Technology (Skoltech)
Clement Fortin
Affiliation:
Skolkovo Institute of Science and Technology (Skoltech)
*
Brovar, Yana, Skolkovo Institute of Science and Technology (Skoltech), Systems Engineering, Russian Federation, yana.brovar@skoltech.ru

Abstract

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Understanding emergence is an important goal of system thinking, as it can express both desirable and negative properties of products and systems. Emergence has also a special importance as it has a direct link to the performance of products and systems, and thus has a direct relationship with the quality of life and thus sustainability in our societies. Emergence and system thinking are closely related to engineering design methodologies. In our paper, we develop a more precise definition of emergence through the core principles of systems complementarity that are similarity, irreducibility and sophisticated relationships expressed through the interfaces between systems, subsystems or product components.

We demonstrate the utility of the approach based on an aircraft pylon case study by presenting a detailed definition of an interface design matrix and analyse how pylon subsystems influence emergence. The results have shown that the product can be perfectly represented by a model-based approach supporting interface management and the assessment of system complementarity. In turn, this approach allows to go beyond a qualitative definition of emergence, as it proposes a quantitative approach through the assessment of complementarity.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

Alsalehi, S. (2019), Similarity in Design: A Framework for Evaluation, Master's Thesis, Skolkovo Institute of Science and Technology, Russia. Available at: http://systemarchitect.mit.edu/docs/alsalehi19.pdfGoogle Scholar
Andreasen, M.M., Hansen, C.T. and Cash, P. (2015), Conceptual design: Interpretations, Mindset and Models, Springer, London.10.1007/978-3-319-19839-2CrossRefGoogle Scholar
Michael, Behe J. (2006), Darwin`s Black Box: The Biochemical Challenge to Evolution, New York/London/Toronto/Sydney: Free Press.Google Scholar
Browning, T.R. (2001), “Applying the Design Structure Matrix to System Decomposition and Integration Problems: a Review and New Directions”, IEEE Transactions on Engineering Management, 48, 292-306.10.1109/17.946528CrossRefGoogle Scholar
Crawley, E., Cameron, B. and Selva, D. (2015), System architecture: strategy and product development for complex systems, Prentice Hall Press.Google Scholar
Dori, D. (2002), Object-Process Methodology: A Holistic System Paradigm, Springer.10.1007/978-3-642-56209-9CrossRefGoogle Scholar
Elavarasi, S Anitha, A. J., and Menaga, K. (2014), A survey on semantic similarity measure. International Journal of Research in Advent Technology 2(4), pp. 389398.Google Scholar
Eppinger, S.D. and Browning, T.R. (2012), Design structure matrix methods and applications, MIT press.10.7551/mitpress/8896.001.0001CrossRefGoogle Scholar
Fodeh, S.J., Haddad, A., Brandt, C., Schultz, M. and Krauthammer, M. (2012), “Enhancing Clustering by Exploiting Complementary Data Modalities in the Medical Domain”, IFIP International Conference on Artificial Intelligence Applications and Innovations, Springer, Berlin, Heidelberg, pp. 357367.10.1007/978-3-642-33409-2_37CrossRefGoogle Scholar
Fortin, C., Sanschagrin, B., Huet, G. and Gagné, S. (2006), “The CAMAQ Project: A Design-Build Experience based on a Virtual Immersion in Aerospace Industry practices”, Journal World Transactions on Engineering and Technology Education, Volume 5, Issue 2.Google Scholar
Fosse, E. and Delp, C.L. (2013), “Systems engineering interfaces: A model based approach”, IEEE Aerospace Conference, 18. https://dx.doi.org/10.1109/AERO.2013.6497322CrossRefGoogle Scholar
Friedenthal, S., Moore, A. and Steiner, R. (2014), A practical guide to SysML: the systems modeling language, Morgan Kaufmann.Google Scholar
Gagné, S. and Fortin, C. (2007), “Application of the CMII model to an integrated engineering and manufacturing development environment”, International Journal on Interactive Design and Manufacturing (IJIDeM), 1(1), pp. 5-13.10.1007/s12008-007-0002-8CrossRefGoogle Scholar
Henkel, R., Hoehndorf, R., Kacprowski, T., Knu, C., Liebermeister, W., and Waltemath, D. (2018), Notions of similarity for systems biology models, vol. 19, no. May 2016, pp. 7788.Google ScholarPubMed
Hosseinie, R. and Mahzoon, M. (2011), “Irreducibility and emergence in complex systems and the quest for alternative insights”, Complexity, 17(2), pp. 10-18.10.1002/cplx.20377CrossRefGoogle Scholar
Huet, G., Pellerin, R., Fortin, C., McSorley, G., and Toche, B. (2010), “Information Structures and Processes to Support Data Exchange between Product Development and Production Planning & Execution Systems”, Journal of Operations and Logistics, 4 (3), pp. 29-38Google Scholar
ISO 19450 (2015), Automation systems and integration — Object-Process Methodology. [online] International Organization for Standardization. Available at: https://www.iso.org/standard/62274.html (accessed date: November 18, 2020).Google Scholar
Maier, J.F., Eckert, C.M. and Clarkson, P.J. (2016), “Model granularity and related concepts”, Proceedings of the 14th International DESIGN Conference, Dubrovnik, Croatia.Google Scholar
Maier, M.W. (1998), “Architecting principles for systems-of-systems”, Systems Engineering, 1, pp. 267284.10.1002/(SICI)1520-6858(1998)1:4<267::AID-SYS3>3.0.CO;2-D3.0.CO;2-D>CrossRefGoogle Scholar
Maier, J.R.A. and Fadel, G.M. (2009), “Affordance-based design methods for innovative design, redesign and reverse engineering”, Research in Engineering Design, 20(4), p. 225.10.1007/s00163-009-0064-7CrossRefGoogle Scholar
Menshenin, Y. and Crawley, E. (2018), “DSM-Based Methods to Represent Specialization Relationships in a Concept Framework”, In 20th International DSM Conference, pp. 151157.Google Scholar
Mikkola, J.H. (2001), “Modularity and interface management of product architectures”, International Conference on Management of Engineering and Technology, PICMET’01. Portland, pp. 599609.Google Scholar
Mittal, S. and Rainey, L. (2015), “Harnessing emergence: the control and design and emergent behavior in system of systems engineering”, SummerSim: summer simulation multi-conference 2015, Chicago, USA.Google Scholar
NASA (2016), Systems Engineering Handbook.Google Scholar
Pickton, D. and Broderick, A. (2006), Integrated Marketing Communications, 3rd edition, Financial Times Prentice HallGoogle Scholar
Pimmler, T. U. and Eppinger, S. D. (1994), “Integration analysis of product decompositions”, Working papers 3690-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.10.1115/DETC1994-0034CrossRefGoogle Scholar
Rahmani, K. and Thomson, V. (2012), “Ontology based interface design and control methodology for collaborative product development”, Computer-Aided Design, 44(5), pp. 432444. https://doi.org/10.1016/j.cad.2011.12.002CrossRefGoogle Scholar
Sosa, M. E., Eppinger, S. D. and Rowles, C. M. (2003), “Identifying Modular and Integrative Systems and Their Impact on Design Team Interactions”, ASME Journal of Mechanical Design, 125(2), pp. 240252.10.1115/1.1564074CrossRefGoogle Scholar
Stephan, A. (2002), “Emergentism, Irreducibility, and Downward causation”, Grazer Philosophishe Studien, vol.65, p. 7793.10.1163/18756735-90000794CrossRefGoogle Scholar
Zeigler, B., Muzy, A. and Yilmaz, L. (2009), “Artificial Intelligence in Modeling and Simulation”, In Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_24Google Scholar
Zheng, C., Le Duigou, J., Bricogne, M. and Eynard, B. (2015), “Multidisciplinary interface model for design of mechatronic systems”, Computers in Industry, 76, pp. 24-3710.1016/j.compind.2015.12.002CrossRefGoogle Scholar