IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v304y2021i1d10.1007_s10479-021-04093-1.html
   My bibliography  Save this article

A two-stage reliability optimization approach for solving series–parallel redundancy allocation problem considering the sale of worn-out parts

Author

Listed:
  • Bakhtiar Ostadi

    (Tarbiat Modares University)

  • Ramtin Hamedankhah

    (Tarbiat Modares University)

Abstract

Redundancy allocation is one of the methods of enhancing the reliability of a system. The components are specified and located based on a non-linear problem. In all problems, a few subsystems are selected to add the parts. Then, the allocation takes place and the new value of reliability is measured. Designers considered a constraint for reliability, and problem-solving at zero time is not the best strategy. Since the reliability decreases over time, this study focused on an approach for two stage reliability optimization to solve series–parallel redundancy allocation problem considering sale of worn-out parts. One a portion of the budget will be spent on maximizing reliability as the system is launched. Other; the reliability reaches its minimum acceptable value, while the remaining budget will be spent on replacement of system’s parts. When a component of the system is replaced earlier than its lifetime, the available budget can be expanded based on the book value of the component. In fact, this model allows the sales of components used in this model. Moreover, the replacement time is calculated based on the constraint set for the level of reliability. It has also highlighted that the cost is significantly reduced with the proposed approach. In this model, both the solution and results are used at zero time. Finally, the mathematical model is examined by an example.

Suggested Citation

  • Bakhtiar Ostadi & Ramtin Hamedankhah, 2021. "A two-stage reliability optimization approach for solving series–parallel redundancy allocation problem considering the sale of worn-out parts," Annals of Operations Research, Springer, vol. 304(1), pages 381-396, September.
  • Handle: RePEc:spr:annopr:v:304:y:2021:i:1:d:10.1007_s10479-021-04093-1
    DOI: 10.1007/s10479-021-04093-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-021-04093-1
    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/s10479-021-04093-1?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. 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.
    2. 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.
    3. Cheng-Fu Huang, 2019. "Evaluation of system reliability for a stochastic delivery-flow distribution network with inventory," Annals of Operations Research, Springer, vol. 277(1), pages 33-45, June.
    4. Kim, Heungseob & Kim, Pansoo, 2017. "Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 153-160.
    5. Mingchih Chen & Xufeng Zhao & Toshio Nakagawa, 2019. "Replacement policies with general models," Annals of Operations Research, Springer, vol. 277(1), pages 47-61, June.
    6. Abdollahzadeh, Hadi & Atashgar, Karim & Abbasi, Morteza, 2016. "Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups," Renewable Energy, Elsevier, vol. 88(C), pages 247-261.
    7. Ha, Chunghun & Kuo, Way, 2006. "Reliability redundancy allocation: An improved realization for nonconvex nonlinear programming problems," European Journal of Operational Research, Elsevier, vol. 171(1), pages 24-38, May.
    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. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

    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. Peiravi, Abdossaber & Ardakan, Mostafa Abouei & Zio, Enrico, 2020. "A new Markov-based model for reliability optimization problems with mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    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. Ouyang, Zhiyuan & Liu, Yu & Ruan, Sheng-Jia & Jiang, Tao, 2019. "An improved particle swarm optimization algorithm for reliability-redundancy allocation problem with mixed redundancy strategy and heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 62-74.
    4. Guilani, Pardis Pourkarim & Juybari, Mohammad N. & Ardakan, Mostafa Abouei & Kim, Heungseob, 2020. "Sequence optimization in reliability problems with a mixed strategy and heterogeneous backup scheme," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Wang, Wei & Lin, Mingqiang & Fu, Yongnian & Luo, Xiaoping & Chen, Hanghang, 2020. "Multi-objective optimization of reliability-redundancy allocation problem for multi-type production systems considering redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    6. Golmohammadi, Elnaz & Ardakan, Mostafa Abouei, 2022. "Reliability optimization problem with the mixed strategy, degrading components, and a periodic inspection and maintenance policy," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    7. Mohammad N Juybari & Mostafa Abouei Ardakan & Hamed Davari-Ardakani, 2019. "A penalty-guided fractal search algorithm for reliability–redundancy allocation problems with cold-standby strategy," Journal of Risk and Reliability, , vol. 233(5), pages 775-790, October.
    8. 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.
    9. Xian Zhao & Jing Zhang & Xiaoyue Wang, 2019. "Joint optimization of components redundancy, spares inventory and repairmen allocation for a standby series system," Journal of Risk and Reliability, , vol. 233(4), pages 623-638, August.
    10. Li, Shuai & Chi, Xuefen & Yu, Baozhu, 2022. "An improved particle swarm optimization algorithm for the reliability–redundancy allocation problem with global reliability," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    11. Seyed Mohsen Mousavi & Najmeh Alikar & Madjid Tavana & Debora Di Caprio, 2019. "An improved particle swarm optimization model for solving homogeneous discounted series-parallel redundancy allocation problems," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1175-1194, March.
    12. Caserta, Marco & Voß, Stefan, 2015. "An exact algorithm for the reliability redundancy allocation problem," European Journal of Operational Research, Elsevier, vol. 244(1), pages 110-116.
    13. Wang, Wei & Wu, Zhiying & Xiong, Junlin & Xu, Yaofeng, 2018. "Redundancy optimization of cold-standby systems under periodic inspection and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 394-402.
    14. Marco Caserta & Stefan Voß, 2016. "A corridor method based hybrid algorithm for redundancy allocation," Journal of Heuristics, Springer, vol. 22(4), pages 405-429, August.
    15. Coit, David W. & Zio, Enrico, 2019. "The evolution of system reliability optimization," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    16. 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.
    17. Li, Yan-Fu & Zhang, Hanxiao, 2022. "The methods for exactly solving redundancy allocation optimization for multi-state series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    18. Ardakan, Mostafa Abouei & Amini, Hanieh & Juybari, Mohammad N., 2022. "Prescheduled switching time: A new strategy for systems with standby components," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    19. Anushri Maji & Asoke Kumar Bhunia & Shyamal Kumar Mondal, 2022. "A production-reliability-inventory model for a series-parallel system with mixed strategy considering shortage, warranty period, credit period in crisp and stochastic sense," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 862-907, September.
    20. Huang, Xianzhen & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2019. "A heuristic survival signature based approach for reliability-redundancy allocation," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 511-517.

    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:annopr:v:304:y:2021:i:1:d:10.1007_s10479-021-04093-1. 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.