IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i20p2547-d653606.html
   My bibliography  Save this article

Reliability Simulation of Two Component Warm-Standby System with Repair, Switching, and Back-Switching Failures under Three Aging Assumptions

Author

Listed:
  • Kiril Tenekedjiev

    (Australian Maritime College, University of Tasmania, 1 Maritime Way, Launceston, TAS 7250, Australia
    Nikola Vaptsarov Naval Academy—Varna, 73 V. Drumev Str., 9002 Varna, Bulgaria)

  • Simon Cooley

    (Australian Maritime College, University of Tasmania, 1 Maritime Way, Launceston, TAS 7250, Australia)

  • Boyan Mednikarov

    (Nikola Vaptsarov Naval Academy—Varna, 73 V. Drumev Str., 9002 Varna, Bulgaria)

  • Guixin Fan

    (Australian Maritime College, University of Tasmania, 1 Maritime Way, Launceston, TAS 7250, Australia)

  • Natalia Nikolova

    (Australian Maritime College, University of Tasmania, 1 Maritime Way, Launceston, TAS 7250, Australia
    Nikola Vaptsarov Naval Academy—Varna, 73 V. Drumev Str., 9002 Varna, Bulgaria)

Abstract

We analyze the influence of repair on a two-component warm-standby system with switching and back-switching failures. The repair of the primary component follows a minimal process, i.e., it experiences full aging during the repair. The backup component operates only while the primary component is being repaired, but it can also fail in standby, in which case there will be no repair for the backup component (as there is no indication of the failure). Four types of system failures are investigated: both components fail to operate in a different order or one of two types of switching failures occur. The reliability behavior of the system is investigated under three different aging assumptions for the backup component during warm-standby: full aging, no aging, and partial aging. Four failure and repair distributions determine the reliability behavior of the system. We analyzed two cases—in the First Case, we utilized constant failure rate distributions. In the Second Case, we applied the more realistic time-dependent failure rates. We used three methods to identify the reliability characteristics of the system: analytical, numerical, and simulational. The analytical approach is limited and only viable for constant failure rate distributions i.e., the First Case. The numerical method integrates simultaneous Algebraic Differential Equations. It produces a solution in the First Case under any type of aging, and in the Second Case but only under the assumption of full aging in warm-standby. On the other hand, the developed simulation algorithms produce solutions for any set of distributions (i.e., the First Case and the Second Case) under any of the three aging assumptions for the backup component in standby. The simulation solution is quantitively verified by comparison with the other two methods, and qualitatively verified by comparing the solutions under the three aging assumptions. It is numerically proven that the full aging and no aging solutions could serve as bounds of the partial aging case even when the precise mechanism of partial aging is unknown.

Suggested Citation

  • Kiril Tenekedjiev & Simon Cooley & Boyan Mednikarov & Guixin Fan & Natalia Nikolova, 2021. "Reliability Simulation of Two Component Warm-Standby System with Repair, Switching, and Back-Switching Failures under Three Aging Assumptions," Mathematics, MDPI, vol. 9(20), pages 1-40, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:20:p:2547-:d:653606
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/20/2547/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/20/2547/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hausken, Kjell, 2008. "Strategic defense and attack for series and parallel reliability systems," European Journal of Operational Research, Elsevier, vol. 186(2), pages 856-881, April.
    2. Attar, Ahmad & Raissi, Sadigh & Khalili-Damghani, Kaveh, 2017. "A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 177-191.
    3. Jiang, R., 2013. "A new bathtub curve model with a finite support," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 44-51.
    4. Xiaohu Li & Zhengcheng Zhang & Yudan Wu, 2009. "Some new results involving general standby systems," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(5), pages 632-642, September.
    5. William Horrace, 2015. "Moments of the truncated normal distribution," Journal of Productivity Analysis, Springer, vol. 43(2), pages 133-138, April.
    6. Wells, Charles E., 2014. "Reliability analysis of a single warm-standby system subject to repairable and nonrepairable failures," European Journal of Operational Research, Elsevier, vol. 235(1), pages 180-186.
    7. Hausken, Kjell, 2008. "Strategic defense and attack for reliability systems," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1740-1750.
    8. Badía, F.G. & Berrade, M.D. & Cha, Ji Hwan & Lee, Hyunju, 2018. "Optimal replacement policy under a general failure and repair model: Minimal versus worse than old repair," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 362-372.
    9. R. K. Bhardwaj & Komaldeep Kaur & S. C. Malik, 2017. "Reliability indices of a redundant system with standby failure and arbitrary distribution for repair and replacement times," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 423-431, June.
    10. Abouei Ardakan, Mostafa & Rezvan, Mohammad Taghi, 2018. "Multi-objective optimization of reliability–redundancy allocation problem with cold-standby strategy using NSGA-II," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 225-238.
    11. S. Srinivasan & R. Subramanian, 2006. "Reliability analysis of a three unit warm standby redundant system with repair," Annals of Operations Research, Springer, vol. 143(1), pages 227-235, March.
    Full references (including those not matched with items on IDEAS)

    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. Subhasish M. Chowdhury & Iryna Topolyan, 2013. "The Attack-and-Defence Group Contests," University of East Anglia Applied and Financial Economics Working Paper Series 049, School of Economics, University of East Anglia, Norwich, UK..
    2. Zaretalab, Arash & Sharifi, Mani & Guilani, Pedram Pourkarim & Taghipour, Sharareh & Niaki, Seyed Taghi Akhavan, 2022. "A multi-objective model for optimizing the redundancy allocation, component supplier selection, and reliable activities for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Subhasish Chowdhury & Dan Kovenock & Roman Sheremeta, 2013. "An experimental investigation of Colonel Blotto games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(3), pages 833-861, April.
    4. Hausken, Kjell & Levitin, Gregory, 2009. "Minmax defense strategy for complex multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 577-587.
    5. Szidarovszky, Ferenc & Luo, Yi, 2014. "Incorporating risk seeking attitude into defense strategy," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 104-109.
    6. Levitin, Gregory & Hausken, Kjell, 2009. "Intelligence and impact contests in systems with redundancy, false targets, and partial protection," Reliability Engineering and System Safety, Elsevier, vol. 94(12), pages 1927-1941.
    7. Shan, Xiaojun & Zhuang, Jun, 2013. "Hybrid defensive resource allocations in the face of partially strategic attackers in a sequential defender–attacker game," European Journal of Operational Research, Elsevier, vol. 228(1), pages 262-272.
    8. Liang, Liang & Chen, Jingxian & Siqueira, Kevin, 2020. "Revenge or continued attack and defense in defender–attacker conflicts," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1180-1190.
    9. Gallice, Andrea, 2017. "An approximate solution to rent-seeking contests with private information," European Journal of Operational Research, Elsevier, vol. 256(2), pages 673-684.
    10. Levitin, Gregory & Hausken, Kjell, 2008. "Protection vs. redundancy in homogeneous parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1444-1451.
    11. Daniel G. Arce & Dan Kovenock J. & Brian Roberson, 2009. "Suicide Terrorism and the Weakest Link," CESifo Working Paper Series 2753, CESifo.
    12. Dan Kovenock & Brian Roberson & Roman M. Sheremeta, 2019. "The attack and defense of weakest-link networks," Public Choice, Springer, vol. 179(3), pages 175-194, June.
    13. Song, Cen & Zhuang, Jun, 2017. "N-stage security screening strategies in the face of strategic applicants," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 292-301.
    14. Hunt, Kyle & Zhuang, Jun, 2024. "A review of attacker-defender games: Current state and paths forward," European Journal of Operational Research, Elsevier, vol. 313(2), pages 401-417.
    15. Ben Yaghlane, Asma & Azaiez, M. Naceur, 2017. "Systems under attack-survivability rather than reliability: Concept, results, and applications," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1156-1164.
    16. 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.
    17. Dan Kovenock & Brian Roberson, 2018. "The Optimal Defense Of Networks Of Targets," Economic Inquiry, Western Economic Association International, vol. 56(4), pages 2195-2211, October.
    18. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    19. Shakun D. Mago & Roman M. Sheremeta, 2019. "New Hampshire Effect: behavior in sequential and simultaneous multi-battle contests," Experimental Economics, Springer;Economic Science Association, vol. 22(2), pages 325-349, June.
    20. Sushil Gupta & Martin K. Starr & Reza Zanjirani Farahani & Mahsa Mahboob Ghodsi, 2020. "Prevention of Terrorism–An Assessment of Prior POM Work and Future Potentials," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1789-1815, July.

    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:gam:jmathe:v:9:y:2021:i:20:p:2547-:d:653606. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.