IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v180y2018icp266-276.html
   My bibliography  Save this article

Reliability allocation model and algorithm for phased mission systems with uncertain component parameters based on importance measure

Author

Listed:
  • Wu, Xin-yang
  • Wu, Xiao-yue
  • Balakrishnan, Narayanaswamy

Abstract

This paper presents a model to deal with reliability allocation problem of phased mission systems (PMS), especially for PMS with uncertainty in components’ parameters due to inaccurate information and different phase environments. In practice, real value of the reliability of a component may become lower than its designed value due to such uncertainty, thus making the whole system fail to meet the required reliability level. Therefore, in this paper, we present a model that incorporates the component uncertainty in the system reliability allocation process and then propose a variance-based global importance hybrid heuristic algorithm for its solution. The variance-based global importance measure is used to evaluate the importance of a component to the mission reliability of PMS while the reliabilities of all components vary randomly. The main procedures of the proposed algorithm include: (1) generate feasible solutions by roulette wheel selection method based on a global importance index; (2) improve solutions by adjusting reliability parameter values of components according to their global importance; and (3) improve solutions by crossover and mutation operations of genetic algorithm (GA). To illustrate the effectiveness of the proposed model and algorithm, two examples of PMS are presented and the allocation solutions are validated through Monte–Carlo simulation method. Finally, we compare the proposed model with a general allocation model that does not consider component uncertainty, and additionally with a cost-based heuristic algorithm and a particle swarm optimization (PSO) algorithm. Our results show that component uncertainty has significant influence on the confidence level that an allocation solution satisfies the required system reliability. Hence, it is essential to consider component uncertainty in reliability allocation process. In comparison with the cost heuristic algorithm and the PSO algorithm, the proposed algorithm is more effective in reliability allocation of PMS with uncertainty in components’ parameters.

Suggested Citation

  • Wu, Xin-yang & Wu, Xiao-yue & Balakrishnan, Narayanaswamy, 2018. "Reliability allocation model and algorithm for phased mission systems with uncertain component parameters based on importance measure," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 266-276.
  • Handle: RePEc:eee:reensy:v:180:y:2018:i:c:p:266-276
    DOI: 10.1016/j.ress.2018.07.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017302442
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2018.07.022?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. Vaurio, J.K., 2011. "Importance measures for multi-phase missions," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 230-235.
    2. Chatwattanasiri, Nida & Coit, David W. & Wattanapongsakorn, Naruemon, 2016. "System redundancy optimization with uncertain stress-based component reliability: Minimization of regret," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 73-83.
    3. Zhang, Enze & Chen, Qingwei, 2016. "Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 83-92.
    4. Wattanapongskorn, Naruemon & Coit, David W., 2007. "Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 92(4), pages 395-407.
    5. Ye, Zhisheng & Li, Zhizhong & Xie, Min, 2010. "Some improvements on adaptive genetic algorithms for reliability-related applications," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 120-126.
    6. Zhao, Ruiqing & Liu, Baoding, 2004. "Redundancy optimization problems with uncertainty of combining randomness and fuzziness," European Journal of Operational Research, Elsevier, vol. 157(3), pages 716-735, September.
    7. Andrews, J.D., 2008. "Birnbaum and criticality measures of component contribution to the failure of phased missions," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1861-1866.
    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. Behzad Karimi & Seyed Taghi Akhavan Niaki & Seyyed Masih Miriha & Mahsa Ghare Hasanluo & Shima Javanmard, 2019. "A weighted K-means clustering approach to solve the redundancy allocation problem of systems having components with different failures," Journal of Risk and Reliability, , vol. 233(6), pages 925-942, December.
    2. Li, Xiang-Yu & Li, Xiaopeng & Feng, Jianxiang & Li, Congming & Xiong, Xiaoyan & Huang, Hong-Zhong, 2023. "Reliability analysis and optimization of multi-phased spaceflight with backup missions and mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Hongyan Dui & Huiting Xu & Yun-An Zhang, 2022. "Reliability Analysis and Redundancy Optimization of a Command Post Phased-Mission System," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
    4. Liu, Mingli & Wang, Dan & Si, Shubin, 2023. "Mixed reliability importance-based solving algorithm design for the cost-constrained reliability optimization model," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    5. Liu, Mingli & Wang, Dan & Si, Shubin, 2024. "Solving algorithm design for the cost minimization reliability optimization model driven by a novel cost-based importance measure," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    6. Lyu, Dong & Si, Shubin, 2021. "Importance measure for K-out-of-n: G systems under dynamic random load considering strength degradation," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    7. Liu, Mingli & Wang, Dan & Zhao, Jiangbin & Si, Shubin, 2022. "Importance measure construction and solving algorithm oriented to the cost-constrained reliability optimization model," Reliability Engineering and System Safety, Elsevier, vol. 222(C).

    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. Behzad Karimi & Seyed Taghi Akhavan Niaki & Seyyed Masih Miriha & Mahsa Ghare Hasanluo & Shima Javanmard, 2019. "A weighted K-means clustering approach to solve the redundancy allocation problem of systems having components with different failures," Journal of Risk and Reliability, , vol. 233(6), pages 925-942, December.
    2. Cao, Ran & Coit, David W. & Hou, Wei & Yang, Yushu, 2020. "Game theory based solution selection for multi-objective redundancy allocation in interval-valued problem parameters," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    3. Serkan Eryilmaz, 2013. "Component importance for linear consecutive‐ k ‐Out‐of‐ n and m ‐Consecutive‐ k ‐Out‐of‐ n systems with exchangeable components," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(4), pages 313-320, June.
    4. Ling, Chunyan & Yang, Lechang & Feng, Kaixuan & Kuo, Way, 2023. "Survival signature based robust redundancy allocation under imprecise probability," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    5. Zhai, Qingqing & Yang, Jun & Zhao, Yu, 2014. "Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 66-82.
    6. 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).
    7. Ghorbani, Milad & Nourelfath, Mustapha & Gendreau, Michel, 2022. "A two-stage stochastic programming model for selective maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    8. 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.
    9. Lingling Bin & Haiyang Pan & Li He & Jijian Lian, 2019. "An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs," Energies, MDPI, vol. 12(22), pages 1-22, November.
    10. Fu, Yuqiang & Wang, Jun, 2022. "Optimum periodic maintenance policy of repairable multi-component system with component reallocation and system overhaul," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    11. Soheil Azizi & Milad Mohammadi, 2023. "Strategy selection for multi-objective redundancy allocation problem in a k-out-of-n system considering the mean time to failure," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 1021-1044, June.
    12. Kim, Heungseob, 2017. "Optimal reliability design of a system with k-out-of-n subsystems considering redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 572-582.
    13. Alikar, Najmeh & Mousavi, Seyed Mohsen & Raja Ghazilla, Raja Ariffin & Tavana, Madjid & Olugu, Ezutah Udoncy, 2017. "Application of the NSGA-II algorithm to a multi-period inventory-redundancy allocation problem in a series-parallel system," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 1-10.
    14. 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.
    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. Altiparmak, Fulya & Dengiz, Berna, 2009. "A cross entropy approach to design of reliable networks," European Journal of Operational Research, Elsevier, vol. 199(2), pages 542-552, December.
    17. Yang, Bo & Li, Xiang & Xie, Min & Tan, Feng, 2010. "A generic data-driven software reliability model with model mining technique," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 671-678.
    18. Fiondella, Lance & Lin, Yi-Kuei & Pham, Hoang & Chang, Ping-Chen & Li, Chendong, 2017. "A confidence-based approach to reliability design considering correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 102-114.
    19. Levitin, Gregory & Finkelstein, Maxim & Xiang, Yanping, 2020. "Optimal aborting rule in multi-attempt missions performed by multicomponent systems," European Journal of Operational Research, Elsevier, vol. 283(1), pages 244-252.
    20. Zhu, Xiaoyan & Fu, Yuqiang & Yuan, Tao & Wu, Xinying, 2017. "Birnbaum importance based heuristics for multi-type component assignment problems," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 209-221.

    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:eee:reensy:v:180:y:2018:i:c:p:266-276. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.