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A Landscape of Trades: The Importance of Process, Ilities, and Practice

Abstract

Tradespace analysis and all of the activities and elements required to make it successful across the various levels and domains is a highly challenging area. At their core, tradespaces are decision spaces. Tradespace creation, exploration, analysis, and the associated methods, processes, and tools that support them will vary in scope, purpose, respect the level of effort required to generate a tradespace appropriate to the stage of analysis, and always be crafted to produce steps forward in terms of building on or adding to the previously existing bodies of knowledge. This chapter will introduce these concepts and discuss the different needs across the Defense enterprise, operational, and system levels of analysis. The chapter will also present the highly challenging problem of system qualities (the “ilities”), which represent major stakeholder needs, but are a major source of project overruns and failures, stakeholder value conflicts, and are poorly defined and understood. System qualities provide a lens to aid our understanding of the difficult nature of bridging the operational and system-intrinsic viewpoints, each with their own needs and completely different levels of abstraction with respect to trades and yet are still co-dependent. Further, the systems engineering community must continue to develop new architectural or other descriptions to relate complex relationships across operational and system-intrinsic views, which is especially vital for new capabilities derived from software or artificial intelligence.


Leads

Valerie B. Sitterle

Georgia Tech Research Institute

Gary Witus

Wayne State University

Publications

  1. Anyanhun, A., Matteson, W., Flemming, C. et al. (2022). An MBSE approach to evaluating architecture specifications for MOSA compliance. In: 25th Annual Systems and Mission Engineering Conference, Orlando, FL (1–3 November 2022). National Defense Industrial Association.

  2. Baker, J., Sitterle, V., Fullmer, D., and Browne, D. (2020). Application of probabilistic graph models to kill chain and multi-domain kill web analysis problems. In: 2020 Virtual Systems and Mission Engineering Conference (10–13 November 2020). National Defense Industrial Association, (Virtual).

  3. Blair, M.D., Nieto-Gomez, R., and Sitterle, V. (2013). Technology, Society, and the Adaptive Nature of Terrorism: Implications for Counterterror. This report represents the views and opinions of the contributing authors. The report does not represent official USG policy or position. UNCLASSIFIED.

  4. Boehm, B. (2006). Some future trends and implications for systems and software engineering processes. Systems Engineering 9 (1): 1–19.

  5. Boehm, B. (2015).Architecture-based quality attribute synergies and conflicts. In: 2015 IEEE/ACM 2nd International Workshop on Software Architecture and Metrics (16 May 2015), 29–34. Washington, DC: IEEE Computer Society.

  6. Boehm, B. and Kukreja, N. (2017). An initial ontology for system qualities. Insight 20 (3): 18–28.

  7. Boehm, B., Chen, C., Srisopha, K., and Shi, L. (2016). The key roles of maintainability in an ontology for system qualities. In: INCOSE International Symposium, Edinburgh, Scotland (18–21 July 2016), vol. 26, No. 1, 2026–2040. San Diego, CA: International Council on Systems Engineering.

  8. Boehm, B. (2019). System Qualities Ontology, Tradespace, and Affordability (SQOTA). Technical Report SERC-2019-TR-012. Stevens Institute of Technology, Systems Engineering Research Center Hoboken United States.

  9. Cellucci, T.A. (2008). Developing Operational Requirements: A Guide to the Cost Effective and Efficient Communication of Needs. US Department of Homeland Security, Washington, DC. UNCLASSIFIED.

  10. Collopy, P., and Sitterle, V. (2019). Validation of AI-Enabled and Autonomous Learning Systems. Technical Report SERC-2019-TR-017. Stevens Institute of Technology, Systems Engineering Research Center Hoboken United States.

  11. Collopy, P., Sitterle, V., and Petrillo, J. (2020). Validation testing of autonomous learning systems. Insight 23 (1): 48–51.

  12. Dahmann, J. (2014). 1.4. 3 System of systems pain points. In: INCOSE International Symposium, Las Vegas, NV (30 June–3 July 2014), vol. 24, No. 1, 108–121. San Diego, CA: International Council on Systems Engineering.

  13. Defense Acquisitions University (2023). Department of Defense DAU glossary of defense acquisition acronyms and terms. https://www.dau.edu/glossary/Pages/Glossary.aspx (Accessed 27 January 2023).

  14. Department of Defense (2016). DOD Dictionary of Military and Associated Terms. DoD Dictionary of Military and Associated Terms. JP 1-02, 8 Nov 2010 (as amended through 15 Feb 2016).

  15. Deputy CTO for Mission Capabilities (2023). Mission engineering. https://ac.cto.mil/mission-engineering (accessed 8 Feb 2023).

  16. Felder, W.N. and Collopy, P. (2012). The elephant in the mist: What we don’t know about the design, development, test and management of complex systems. Journal of Aerospace Operations 1 (4): 317–327.

  17. Haimes, Y.Y. (2012). Systems-based guiding principles for risk modeling, planning, assessment, management, and communication. Risk Analysis: An International Journal 32 (9): 1451–1467.

  18. Harvey, A. S. (2021). The levels of war as levels of analysis. Military Review.

  19. Koh, E.C., Caldwell, N.H., and Clarkson, P.J. (2013). A technique to assess the changeability of complex engineering systems. Journal of Engineering Design 24 (7): 477–498.

  20. Lane, J.A., Koolmanojwong, S., and Boehm, B. (2013). 4.6. 3 Affordable systems: balancing the capability, schedule, flexibility, and technical debt tradespace. In: INCOSE International Symposium, Philadelphia, PA (24–27 June 2013), vol. 23, No. 1, 1385–1399. San Diego, CA: International Council on Systems Engineering.

  21. Menzel, C.P., Mayer, R.J., and Painter, M.K. (1992). IDEF5 ontology Description Capture Method: Concepts and Formal Foundations. Texas A and M Univ College Station Knowledge Based Systems Lab.

  22. Mesmer, B., Shapiro, D., Petrillo, J. et al. (2021). Validation Framework for Assuring Adaptive and Learning-Enabled Systems. Technical Report SERC-2021-TR-021. Stevens Institute of Technology, Systems Engineering Research Center Hoboken United States.

  23. Miller, E.B. (2018). DoD Principles on Mission Effectiveness and Spectrum Efficiency. Memorandum for Secretaries of the Military Departments, 3 May 2018.

  24. Ross, A.M. and Rhodes, D.H. (2015). Towards a prescriptive semantic basis for change-type ilities. Procedia Computer Science 44: 443–453.

  25. Ross, A.M. and Rhodes, D.H. (2019). Ilities semantic basis: research progress and future directions. Procedia Computer Science 153: 126–134.

  26. Salado, A. and Nilchiani, R. (2015). A research on measuring and reducing problem complexity to increase system affordability: from theory to practice. Procedia Computer Science 44: 21–30.

  27. Shapero, A. and Bates, C. (1959). A Method for Performing Human Engineering Analysis of Weapon Systems (Vol. 59, No. 784). Wright Air Development Center, Air Research and Development Command, United States Air Force.

  28. Sitterle, V.B., Freeman, D.F., Goerger, S.R., and Ender, T.R. (2015). Systems engineering resiliency: guiding tradespace exploration within an engineered resilient systems context. Procedia Computer Science 44: 649–658.

  29. Sitterle, V.B., Brimhall, E.L., Freeman, D.F. et al. (2017). Bringing operational perspectives into the analysis of engineered resilient systems. Insight 20 (3): 47–55.

  30. Smead, K. (2015). A Descriptive Guide to Trade Space Analysis. Monterey, CA: Army TRADOC Analysis Center.

  31. Stevens, J.S. (2017). Warranting system validity through a holistic validation framework: a research agenda. In: INCOSE International Symposium. (July) (Vol. 27, No. 1, pp. 654–671).

  32. Toulmin, S. and Toulmin, S.E. (1992). Cosmopolis: The Hidden Agenda of Modernity. University of Chicago press.

  33. Toulmin, S.E. (2003). The Uses of Argument. Cambridge University Press; Updated edition. ISBN-13: 978-0521534833.

  34. Walden, D.D., Roedler, G.J., and Forsberg, K. (2015). INCOSE systems engineering handbook version 4: updating the reference for practitioners. In: INCOSE International Symposium. (October) (Vol. 25, No. 1, pp. 678–686).

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The Systems Engineering Research Center (SERC) was established in the Fall of 2008 as a government-designated University Affiliated Research Center (UARC). The SERC has produced 15 years of research, focused on an updated systems engineering toolkit (methods, tools, and practices) for the complex cyber-physical systems of today and tomorrow.


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