IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v39y2019i2d10.1007_s10669-019-09731-5.html
   My bibliography  Save this article

Convergent set-based design for complex resilient systems

Author

Listed:
  • Zephan Wade

    (University of Arkansas)

  • Gregory S. Parnell

    (University of Arkansas)

  • Simon Goerger

    (Engineer Research and Development Center)

  • Ed Pohl

    (University of Arkansas)

  • Eric Specking

    (University of Arkansas)

Abstract

The Department of Defense Engineered Resilient Systems (ERS) goes beyond the concept of resilience as a response to a disruption. The ERS project focuses on improving design agility and cost-effectiveness leading to improvements in systems analysis, development, testing, manufacturing, and fielding of mission-effective and adaptable systems. Point-Based Design (PBD) seeks to select a point as a design baseline and proceed into development. Our research uses Set-Based Design (SBD) for early concept evaluation of engineered systems as an alternative to PBD. SBD seeks to eliminate less cost-effective sets (in the value vs. cost tradespace) and focus on one or more remaining sets during early design. Our research develops a technique called Convergent Set-Based Design (SBD), a procedure for mathematical elimination and improvement of sets of designs. We developed Convergent SBD for the ERS program. Our research includes the capability to measure and quantify mission resilience using probability trees for all system performance measures. Convergent SBD uses dominance identification equations to compare statistical means for value and cost. The demonstration illustrates the effect of adding mission resilience in the design tradespace. Convergent SBD provides a foundational mathematical technique for eliminating less promising design sets and identifying the most promising design sets.

Suggested Citation

  • Zephan Wade & Gregory S. Parnell & Simon Goerger & Ed Pohl & Eric Specking, 2019. "Convergent set-based design for complex resilient systems," Environment Systems and Decisions, Springer, vol. 39(2), pages 118-127, June.
    • Handle: RePEc:spr:envsyd:v:39:y:2019:i:2:d:10.1007_s10669-019-09731-5
    DOI: 10.1007/s10669-019-09731-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-019-09731-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10669-019-09731-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    2. Sabrina Larkin & Cate Fox-Lent & Daniel A. Eisenberg & Benjamin D. Trump & Sean Wallace & Colin Chadderton & Igor Linkov, 2015. "Benchmarking agency and organizational practices in resilience decision making," Environment Systems and Decisions, Springer, vol. 35(2), pages 185-195, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Peter A. Beling & Cody H. Fleming & William T. Scherer, 2019. "Systems engineering in context," Environment Systems and Decisions, Springer, vol. 39(2), pages 109-110, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ivo Häring & Mirjam Fehling-Kaschek & Natalie Miller & Katja Faist & Sebastian Ganter & Kushal Srivastava & Aishvarya Kumar Jain & Georg Fischer & Kai Fischer & Jörg Finger & Alexander Stolz & Tobias , 2021. "A performance-based tabular approach for joint systematic improvement of risk control and resilience applied to telecommunication grid, gas network, and ultrasound localization system," Environment Systems and Decisions, Springer, vol. 41(2), pages 286-329, June.
    2. Eric Specking & Bobby Cottam & Gregory Parnell & Edward Pohl & Matthew Cilli & Randy Buchanan & Zephan Wade & Colin Small, 2019. "Assessing Engineering Resilience for Systems with Multiple Performance Measures," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1899-1912, September.
    3. Fauzan Hanif Jufri & Jun-Sung Kim & Jaesung Jung, 2017. "Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event," Energies, MDPI, vol. 10(11), pages 1-17, November.
    4. Yang, Bofan & Zhang, Lin & Zhang, Bo & Xiang, Yang & An, Lei & Wang, Wenfeng, 2022. "Complex equipment system resilience: Composition, measurement and element analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    5. Francis, Royce & Bekera, Behailu, 2014. "A metric and frameworks for resilience analysis of engineered and infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 90-103.
    6. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    7. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    8. Ruiying Li & Qiang Dong & Chong Jin & Rui Kang, 2017. "A New Resilience Measure for Supply Chain Networks," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    9. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    10. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    11. Jesse M. Keenan, 2018. "Regional resilience trust funds: an exploratory analysis for leveraging insurance surcharges," Environment Systems and Decisions, Springer, vol. 38(1), pages 118-139, March.
    12. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    13. Li, Ruiying & Gao, Ying, 2022. "On the component resilience importance measures for infrastructure systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 36(C).
    14. Haritha, P.C. & Anjaneyulu, M.V.L.R., 2024. "Comparison of topological functionality-based resilience metrics using link criticality," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    15. Ottenburger, Sadeeb Simon & Çakmak, Hüseyin Kemal & Jakob, Wilfried & Blattmann, Andreas & Trybushnyi, Dmytro & Raskob, Wolfgang & Kühnapfel, Uwe & Hagenmeyer, Veit, 2020. "A novel optimization method for urban resilient and fair power distribution preventing critical network states," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    16. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    17. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng, 2021. "Resilient communication model for satellite networks using clustering technique," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    18. Zhou, Xinxin & Huang, Yun & Bai, Guanghan & Xu, Bei & Tao, Junyong, 2024. "The resilience evaluation of unmanned autonomous swarm with informed agents under partial failure," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    19. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Barker, Kash & Moronta, Jose, 2018. "Quantifying the resilience of community structures in networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 466-474.
    20. MacKenzie, Cameron A. & Hu, Chao, 2019. "Decision making under uncertainty for design of resilient engineered systems," Reliability Engineering and System Safety, Elsevier, vol. 192(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:39:y:2019:i:2:d:10.1007_s10669-019-09731-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.