IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v221y2007i2p133-140.html
   My bibliography  Save this article

Reliability and maintainability allocation to minimize total cost of ownership in a series-parallel system

Author

Listed:
  • U. Dinesh Kumar
  • J. E. Ramírez-Márquez
  • D Nowicki
  • D Verma

Abstract

Allocation of system level requirements is most effective when performed early in the system's design phase. This holds especially true for two critical and fundamental design characteristics: reliability and maintainability. Traditional reliability allocation models are developed to either maximize system reliability under a cost constraint or minimize cost subject to a system-level, target reliability constraint. Cost, in these traditional allocation models, is represented solely by unit cost. Unit cost, by itself, is an inadequate measure of a system's operational effectiveness. In fact, the underlying economic metric used to properly describe the operational effectiveness of a system is total cost of ownership (TCO). TCO includes not only the upstream unit cost but the downstream operations, maintenance, and support costs. In this paper, new allocation models are developed based on TCO that simultaneously allocate both reliability and maintainability for a series-parallel system subject to meeting a system-level availability target. A non-linear representation of a mathematical model is defined that simultaneously allocates both system-level reliability and maintainability targets in a manner that minimizes TCO. This non-linear model is then transformed into a surrogate linear model that can be solved using existing commercial software. Examples are then discussed to illustrate the solution procedure and to show the sensitivity of allocation design decisions to fluctuations in economic factors such as discount rates, and design factors such as the life of the system.

Suggested Citation

  • U. Dinesh Kumar & J. E. Ramírez-Márquez & D Nowicki & D Verma, 2007. "Reliability and maintainability allocation to minimize total cost of ownership in a series-parallel system," Journal of Risk and Reliability, , vol. 221(2), pages 133-140, June.
  • Handle: RePEc:sae:risrel:v:221:y:2007:i:2:p:133-140
    DOI: 10.1243/1748006XJRR41
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1243/1748006XJRR41
    Download Restriction: no

    File URL: https://libkey.io/10.1243/1748006XJRR41?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
    ---><---

    References listed on IDEAS

    as
    1. Yalaoui, Alice & Chu, Chengbin & Châtelet, Eric, 2005. "Reliability allocation problem in a series–parallel system," Reliability Engineering and System Safety, Elsevier, vol. 90(1), pages 55-61.
    2. de Castro, Hélio Fiori & Cavalca, Katia Lucchesi, 2006. "Maintenance resources optimization applied to a manufacturing system," Reliability Engineering and System Safety, Elsevier, vol. 91(4), pages 413-420.
    3. Subba Rao V. Majety & Milind Dawande & Jayant Rajgopal, 1999. "Optimal Reliability Allocation with Discrete Cost-Reliability Data for Components," Operations Research, INFORMS, vol. 47(6), pages 899-906, December.
    4. Gen, Mitsuo & Yun, YoungSu, 2006. "Soft computing approach for reliability optimization: State-of-the-art survey," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1008-1026.
    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. Tavakkoli-Moghaddam, R. & Safari, J. & Sassani, F., 2008. "Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 550-556.
    2. Sadjadi, Seyed Jafar & Soltani, R., 2009. "An efficient heuristic versus a robust hybrid meta-heuristic for general framework of serial–parallel redundancy problem," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1703-1710.
    3. Gholinezhad, Hadi & Zeinal Hamadani, Ali, 2017. "A new model for the redundancy allocation problem with component mixing and mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 66-73.
    4. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2013. "Cold-standby sequencing optimization considering mission cost," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 28-34.
    5. Levitin, Gregory & Xing, Liudong & Haim, Hanoch Ben & Dai, Yuanshun, 2019. "Optimal structure of series system with 1-out-of-n warm standby subsystems performing operation and rescue functions," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 523-531.
    6. Safari, Jalal, 2012. "Multi-objective reliability optimization of series-parallel systems with a choice of redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 10-20.
    7. 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).
    8. Peiravi, Abdossaber & Nourelfath, Mustapha & Zanjani, Masoumeh Kazemi, 2022. "Redundancy strategies assessment and optimization of k-out-of-n systems based on Markov chains and genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    9. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2014. "Optimal component loading in 1-out-of-N cold standby systems," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 58-64.
    10. Ranjan Kumar Gupta & Indranil Deb, 2024. "A heuristic application of systems reliability optimization in supplier selection problem of a make-to-order supply chain," 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. 15(12), pages 5742-5755, December.
    11. Chambari, Amirhossain & Najafi, Amir Abbas & Rahmati, Seyed Habib A. & Karimi, Aida, 2013. "An efficient simulated annealing algorithm for the redundancy allocation problem with a choice of redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 158-164.
    12. Balesdent, Mathieu & Morio, Jérôme & Marzat, Julien, 2015. "Recommendations for the tuning of rare event probability estimators," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 68-78.
    13. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2023. "Optimizing partial component activation policy in multi-attempt missions," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    14. Meisam Sadeghi & Emad Roghanian & Hamid Shahriari & Hassan Sadeghi, 2021. "Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies and heterogeneous components: Erlang time-to-failure distribution," Journal of Risk and Reliability, , vol. 235(3), pages 509-528, June.
    15. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2014. "Cold vs. hot standby mission operation cost minimization for 1-out-of-N systems," European Journal of Operational Research, Elsevier, vol. 234(1), pages 155-162.
    16. Zaretalab, Arash & Hajipour, Vahid & Tavana, Madjid, 2020. "Redundancy allocation problem with multi-state component systems and reliable supplier selection," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    17. Levitin, Gregory & Finkelstein, Maxim & Dai, Yuanshun, 2017. "Redundancy optimization for series-parallel phased mission systems exposed to random shocks," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 554-560.
    18. Levitin, Gregory & Xing, Liudong & Peng, Sun & Dai, Yuanshun, 2015. "Optimal choice of standby modes in 1-out-of-N system with respect to mission reliability and cost," Applied Mathematics and Computation, Elsevier, vol. 258(C), pages 587-596.
    19. Alper Atamtürk & Andrés Gómez, 2017. "Maximizing a Class of Utility Functions Over the Vertices of a Polytope," Operations Research, INFORMS, vol. 65(2), pages 433-445, March-Apr.
    20. Khalili-Damghani, Kaveh & Amiri, Maghsoud, 2012. "Solving binary-state multi-objective reliability redundancy allocation series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 35-44.

    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:sae:risrel:v:221:y:2007:i:2:p:133-140. 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: SAGE Publications (email available below). General contact details of provider: .

    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.