Advertisement

Research in Engineering Design

, Volume 28, Issue 1, pp 53–69 | Cite as

Supporting design via the System Operational Dependency Analysis methodology

  • Cesare GuarinielloEmail author
  • Daniel DeLaurentis
Original Paper

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.

Keywords

Dependencies Design Behavioral analysis System architecture Operability Risk System-of-systems 

List of symbols

Oi

Operability of node i

OiC

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

OiS

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

OijC

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

OijS

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

SEi

Self-effectiveness of node i

Wλ

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

αij

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

βij

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

γij

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

Notes

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.

References

  1. Augustine M, Yadav OP, Jain R, Rathore A (2012) Cognitive map-based system modeling for identifying interaction failure modes. Res Eng Des 23:105–124CrossRefGoogle Scholar
  2. 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 15:41–61CrossRefGoogle Scholar
  3. Box GEP, Wilson KB (1951) On the experimental attainment of optimum conditions (with discussion). J R Stat Soc Ser B 13(1):1–45zbMATHGoogle Scholar
  4. 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):292–306CrossRefGoogle Scholar
  5. Chow R, Braun D, Fry D (2012) DAF: discrete agent framework programmer’s manual. Purdue University, West LafayetteGoogle Scholar
  6. Clarkson J, Simons C, Eckert C (2004) Predicting change propagation in complex design. J Mech Des 126:788–797CrossRefGoogle Scholar
  7. Dahmann J, Smith K (2012) Integrating systems engineering and test and evaluation in system of systems development. In: IEEE international systems conference, VancouverGoogle Scholar
  8. de Weck OL, Ross AM, Rhodes DH (2012) Investigating relationships and semantic sets amongst system lifecycle properties (ilities). In: Third international engineering systems symposium. DelftGoogle Scholar
  9. Eppinger S, Browning T (2012) Design structure matrix methods and applications. MIT Press, CambridgeGoogle Scholar
  10. Fang C, Marle F (2012) A simulation-based risk network model for decision support in project risk management. Decis Support Syst 52:635–644CrossRefGoogle Scholar
  11. Gaonkar R, Viswanadham N (2007) Analytical framework for the management of risk in supply chains. IEEE Trans Autom Sci Eng 4(2):265–273CrossRefGoogle Scholar
  12. Garvey P, Pinto A (2009) Introduction to functional dependency network analysis. In: Second international symposium on engineering systems, CambridgeGoogle Scholar
  13. Garvey P, Pinto A (2012) Advanced risk analysis in engineering enterprise systems. CRC Press, Boca RatonzbMATHGoogle Scholar
  14. 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):1–24CrossRefGoogle Scholar
  15. 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 16:265–274Google Scholar
  16. 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 DiegoGoogle Scholar
  17. 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, BeijingGoogle Scholar
  18. 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 28:720–727CrossRefGoogle Scholar
  19. 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 28:728–735CrossRefGoogle Scholar
  20. Haimes YY, Jiang P (2001) Leontief-based model of risk in complex interconnected infrastructures. J Infrastruct Syst 7:1–12CrossRefGoogle Scholar
  21. 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 11:67–79CrossRefGoogle Scholar
  22. 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 CrossRefGoogle Scholar
  23. 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):1581–1590CrossRefGoogle Scholar
  24. 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 VegasGoogle Scholar
  25. INCOSE (2015) Systems engineering handbook: a guide for system life cycle processes and activities. Wiley, HobokenGoogle Scholar
  26. Khuri A, Mukhopadhyay S (2010) Response surface methodology. WIREs. Comput Stat 2(2):128–149CrossRefGoogle Scholar
  27. Kurtoglu T, Tumer I, Jensen D (2010) A functional failure reasoning methodology for evaluation of conceptual system architectures. Res Eng Des 21:209–234CrossRefGoogle Scholar
  28. Maier M (1998) Architecting principles for systems-of-systems. Syst Eng 1(4):267–284CrossRefGoogle Scholar
  29. 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 CrossRefGoogle Scholar
  30. Maurer M, Lindemann U (2008) The application of multiple-domain matrix. In: IEEE international conference on systems, man and cybernetics, pp 2487–2493Google Scholar
  31. McManus H, Hastings D, Warmkessel J (2004) New methods for rapid architecture selection and conceptual design. J Spacecr Rockets 41(1):10–19CrossRefGoogle Scholar
  32. Mearns AB (1965) Fault tree analysis: the study of unlikely events in complex systems. Boeing/UW System Safety SymposiumGoogle Scholar
  33. 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 CrossRefGoogle Scholar
  34. Mour A, Kenley CR, Davendralingam N, DeLaurentis D (2013) Agent-based modeling for systems of systems. INCOSE Int Symp 23(1):973–987CrossRefGoogle Scholar
  35. Nai Fovino I, Masera M (2006) Emergent disservices in interdependent systems and system-of-systems. In: IEEE international conference on systems, man, and cybernetics. TaipeiGoogle Scholar
  36. Nguyen D, Shen Y, Thai M (2013) Detecting critical nodes in interdependent power networks for vulnerability assessment. IEEE Trans Smart Grid 4(1):151–159CrossRefGoogle Scholar
  37. 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):852–875CrossRefGoogle Scholar
  38. Pearl J (1988) Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, San FranciscozbMATHGoogle Scholar
  39. 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. VancouverGoogle Scholar
  40. Rinaldi S, Peerenboom J, Kelly T (2001) Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Syst Mag 21(6):11–25CrossRefGoogle Scholar
  41. 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):325–345Google Scholar
  42. 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):257–269CrossRefGoogle Scholar
  43. Sosa M (2008) A structured approach to predicting and managing technical interactions in software development. Res Eng Des 19:47–70CrossRefGoogle Scholar
  44. Stone RB, Wood KL (2000) Development of a functional basis for design. J Mech Des 122(4):359–370CrossRefGoogle Scholar
  45. Stone RB, Tumer IY, Van Wie M (2005) The function-failure design method. J Mech Des 127(3):397–407CrossRefGoogle Scholar
  46. Taguchi G (1986) Introduction to quality engineering: designing quality into products and processes. Asian Productivity Organization. American Supplier Institute, DearbornGoogle Scholar
  47. Tumer IY, Stone RB (2003) Mapping function to failure mode during component development. Res Eng Des 14(1):25–33CrossRefGoogle Scholar
  48. United States Department of Defense (1949) MIL-P-1629. Procedures for performing a failure mode effect and critical analysisGoogle Scholar
  49. Wang Y, Zhang W, Li Q (2014) Functional dependency network analysis of security of navigation satellite system. Appl Mech Mater 522–524:1192–1196CrossRefGoogle Scholar
  50. Watson HA (1961) Launch control safety study. Bell Labs, Murray HillGoogle Scholar
  51. Zio E, Sansavini G (2011) Modeling interdependent network systems for identifying cascade-safe operating margins. IEEE Trans Reliab 60(1):94–101CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.School of Aeronautics and AstronauticsPurdue UniversityWest LafayetteUSA

Personalised recommendations