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Supporting design via the System Operational Dependency Analysis methodology

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Abstract

In this paper, we introduce the system operational dependency analysis methodology. Its purpose is to assess the effect of dependencies between components in a monolithic complex system, or between systems in a system-of-systems, and to support design decision making. We propose a parametric model of the behavior of the system. This approach results in a simple, intuitive model, whose parameters give a direct insight into the causes of observed, and possibly emergent, behavior. Using the proposed method, designers, and decision makers can quickly analyze and explore the behavior of complex systems and evaluate different architecture under various working conditions. Thus, the system operational dependency analysis method supports educated decision making both in the design and in the update process of systems architecture, without the need to execute extensive simulations. In particular, in the phase of concept generation and selection, the information given by the method can be used to identify promising architectures to be further tested and improved, while discarding architectures that do not show the required level of global features. Application of the proposed method to a small example is used to demonstrate both the validation of the parametric model, and the capabilities of the method for system analysis, design and architecture.

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Abbreviations

O i :

Operability of node i

O C i :

Global term of operability of node i due to criticality of dependency

O S i :

Global term of operability of node i due to strength of dependency

O C ij :

Term of operability of node i due to criticality of dependency from node j

O S ij :

Term of operability of node i due to strength of dependency from node j

SE i :

Self-effectiveness of node i

W λ :

Weight for the term based on criticality of dependency in multiple dependencies

α ij :

Parameter associated to the strength of dependency (SOD) between node i and node j

β ij :

Parameter associated to the criticality of dependency (COD) between node i and node j

γ ij :

Parameter associated to the impact of dependency (IOD) between node i and node j

References

  • Augustine M, Yadav OP, Jain R, Rathore A (2012) Cognitive map-based system modeling for identifying interaction failure modes. Res Eng Des 23:105–124

    Article  Google Scholar 

  • Bartolomei JE, Hastings DE, de Neufville R, Rhodes DH (2012) Engineering systems multiple-domain matrix: an organizing framework for modeling large-scale complex systems. Syst Eng 15:41–61

    Article  Google Scholar 

  • Box GEP, Wilson KB (1951) On the experimental attainment of optimum conditions (with discussion). J R Stat Soc Ser B 13(1):1–45

    MATH  Google Scholar 

  • Browning T (2001) Applying the design structure matrix to system decomposition and integration problems: a review and new directions. IEEE Trans Eng Manag 48(3):292–306

    Article  Google Scholar 

  • Chow R, Braun D, Fry D (2012) DAF: discrete agent framework programmer’s manual. Purdue University, West Lafayette

    Google Scholar 

  • Clarkson J, Simons C, Eckert C (2004) Predicting change propagation in complex design. J Mech Des 126:788–797

    Article  Google Scholar 

  • Dahmann J, Smith K (2012) Integrating systems engineering and test and evaluation in system of systems development. In: IEEE international systems conference, Vancouver

  • de Weck OL, Ross AM, Rhodes DH (2012) Investigating relationships and semantic sets amongst system lifecycle properties (ilities). In: Third international engineering systems symposium. Delft

  • Eppinger S, Browning T (2012) Design structure matrix methods and applications. MIT Press, Cambridge

    Google Scholar 

  • Fang C, Marle F (2012) A simulation-based risk network model for decision support in project risk management. Decis Support Syst 52:635–644

    Article  Google Scholar 

  • Gaonkar R, Viswanadham N (2007) Analytical framework for the management of risk in supply chains. IEEE Trans Autom Sci Eng 4(2):265–273

    Article  Google Scholar 

  • Garvey P, Pinto A (2009) Introduction to functional dependency network analysis. In: Second international symposium on engineering systems, Cambridge

  • Garvey P, Pinto A (2012) Advanced risk analysis in engineering enterprise systems. CRC Press, Boca Raton

    MATH  Google Scholar 

  • Garvey P, Pinto A, Santos JR (2014) Modelling and measuring the operability of interdependent systems and systems of systems: advances in methods and applications. Int J Syst Syst Eng 5(1):1–24

    Article  Google Scholar 

  • Guariniello C, DeLaurentis D (2013a) Dependency analysis of system-of-systems operational and development networks. In: Paredis CJJ, Bishop C, Bodne D (eds) Conference on Systems Engineering Research. Procedia Comput Sci 16:265–274

  • Guariniello C, DeLaurentis D (2013b) Maintenance and recycling in space: functional dependency analysis of on-orbit servicing satellites team for modular spacecraft. In: AIAA Space Conference. San Diego

  • Guariniello C, DeLaurentis D (2013c) Dependency network analysis: fostering the future of space with new tools and techniques in space systems-of-systems design and architecture. IAF International Astronautical Congress, Beijing

    Google Scholar 

  • Guariniello C, DeLaurentis D (2014a) Communications, information, and cyber security in systems-of-systems: assessing the impact of attacks through interdependency analysis. In: Madni AM, Boehm B (eds) Conference on Systems Engineering Research. Procedia Comput Sci 28:720–727

    Article  Google Scholar 

  • Guariniello C, DeLaurentis D (2014b) Integrated analysis of functional and developmental interdependencies to quantify and trade-off ilities for system-of-systems design, architecture, and evolution. In: Madni AM, Boehm B (eds) Conference on Systems Engineering Research. Procedia Comput Sci 28:728–735

    Article  Google Scholar 

  • Haimes YY, Jiang P (2001) Leontief-based model of risk in complex interconnected infrastructures. J Infrastruct Syst 7:1–12

    Article  Google Scholar 

  • Haimes YY, Horowitz BM, Lambert JH, Santos JR, Lian C, Crowther KG (2005) Inoperability input-output model for interdependent infrastructure sectors. I: theory and methodology. J Infrastruct Syst 11:67–79

    Article  Google Scholar 

  • Hamraz B, Caldwell N, Clarkson J (2012) A multidomain engineering change propagation model to support uncertainty reduction in risk management in design. J Mech Des 134(10):100905. doi:10.1115/1.4007397

    Article  Google Scholar 

  • Hsu J, Clymer J, Garcia J, Gonzales E (2009) Agent-based modeling the emergent behavior of a system-of-systems. INCOSE Int Symp 19(1):1581–1590

    Article  Google Scholar 

  • Hutcheson R, McAdams DA, Stone RB, Tumer IY (2007) Function-based behavioral modeling. In: Proceedings of the 2007 ASME design engineering technical conferences and computers and information in engineering conference. Las Vegas

  • INCOSE (2015) Systems engineering handbook: a guide for system life cycle processes and activities. Wiley, Hoboken

    Google Scholar 

  • Khuri A, Mukhopadhyay S (2010) Response surface methodology. WIREs. Comput Stat 2(2):128–149

    Article  Google Scholar 

  • Kurtoglu T, Tumer I, Jensen D (2010) A functional failure reasoning methodology for evaluation of conceptual system architectures. Res Eng Des 21:209–234

    Article  Google Scholar 

  • Maier M (1998) Architecting principles for systems-of-systems. Syst Eng 1(4):267–284

    Article  Google Scholar 

  • Mane M, DeLaurentis D, Frazho A (2011) A Markov perspective on development interdependencies in networks of systems. J Mech Des 133(10):101009. doi:10.1115/1.4004975

    Article  Google Scholar 

  • Maurer M, Lindemann U (2008) The application of multiple-domain matrix. In: IEEE international conference on systems, man and cybernetics, pp 2487–2493

  • McManus H, Hastings D, Warmkessel J (2004) New methods for rapid architecture selection and conceptual design. J Spacecr Rockets 41(1):10–19

    Article  Google Scholar 

  • Mearns AB (1965) Fault tree analysis: the study of unlikely events in complex systems. Boeing/UW System Safety Symposium

  • Moullec ML, Bouissou M, Jankovic M, Bocquet JC, Requillard F, Maas O, Forgeot O (2013) Toward system architecture generation and performance assessment under uncertainty using Bayesian networks. J Mech Des 135(4):041002. doi:10.1115/1.4023514

    Article  Google Scholar 

  • Mour A, Kenley CR, Davendralingam N, DeLaurentis D (2013) Agent-based modeling for systems of systems. INCOSE Int Symp 23(1):973–987

    Article  Google Scholar 

  • Nai Fovino I, Masera M (2006) Emergent disservices in interdependent systems and system-of-systems. In: IEEE international conference on systems, man, and cybernetics. Taipei

  • Nguyen D, Shen Y, Thai M (2013) Detecting critical nodes in interdependent power networks for vulnerability assessment. IEEE Trans Smart Grid 4(1):151–159

    Article  Google Scholar 

  • Nunez M, Datta V, Molina-Cristobal A, Guenov M, Riaz A (2012) Enabling exploration in the conceptual design and optimisation of complex systems. J Eng Des 23(10–11):852–875

    Article  Google Scholar 

  • Pearl J (1988) Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, San Francisco

    MATH  Google Scholar 

  • Rhodes DH, Ross AM, Nightingale DJ (2009) Architecting the system of systems enterprise: enabling constructs and methods from the field of engineering systems. In: IEEE international systems conference. Vancouver

  • Rinaldi S, Peerenboom J, Kelly T (2001) Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Syst Mag 21(6):11–25

    Article  Google Scholar 

  • Sage A, Cuppan C (2001) On the systems engineering and management of systems of systems and federations of systems. Inf Knowl Syst Manag 2(4):325–345

    Google Scholar 

  • Shaw G, Miller D, Hastings D (2001) Development of the quantitative generalized information network analysis (GINA) methodology for satellite systems. J Spacecr Rockets 38(2):257–269

    Article  Google Scholar 

  • Sosa M (2008) A structured approach to predicting and managing technical interactions in software development. Res Eng Des 19:47–70

    Article  Google Scholar 

  • Stone RB, Wood KL (2000) Development of a functional basis for design. J Mech Des 122(4):359–370

    Article  Google Scholar 

  • Stone RB, Tumer IY, Van Wie M (2005) The function-failure design method. J Mech Des 127(3):397–407

    Article  Google Scholar 

  • Taguchi G (1986) Introduction to quality engineering: designing quality into products and processes. Asian Productivity Organization. American Supplier Institute, Dearborn

    Google Scholar 

  • Tumer IY, Stone RB (2003) Mapping function to failure mode during component development. Res Eng Des 14(1):25–33

    Article  Google Scholar 

  • United States Department of Defense (1949) MIL-P-1629. Procedures for performing a failure mode effect and critical analysis

  • Wang Y, Zhang W, Li Q (2014) Functional dependency network analysis of security of navigation satellite system. Appl Mech Mater 522–524:1192–1196

    Article  Google Scholar 

  • Watson HA (1961) Launch control safety study. Bell Labs, Murray Hill

    Google Scholar 

  • Zio E, Sansavini G (2011) Modeling interdependent network systems for identifying cascade-safe operating margins. IEEE Trans Reliab 60(1):94–101

    Article  Google Scholar 

Download references

Acknowledgments

This material is based upon work supported, in whole or in part, by the US Department of Defense through the Systems Engineering Research Center (SERC) under Contract HQ0034-13-D-0004 RT #108. SERC is a federally funded University Affiliated Research Center managed by Stevens Institute of Technology.

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  1. School of Aeronautics and Astronautics, Purdue University, 701 W Stadium Ave, West Lafayette, IN, 47907, USA

    Cesare Guariniello & Daniel DeLaurentis

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  1. Cesare Guariniello
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  2. Daniel DeLaurentis
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Correspondence to Cesare Guariniello.

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Guariniello, C., DeLaurentis, D. Supporting design via the System Operational Dependency Analysis methodology. Res Eng Design 28, 53–69 (2017). https://doi.org/10.1007/s00163-016-0229-0

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