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G-mixed: A new strategy for redundant components in reliability optimization problems

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  • Sedaghat, Niloofar
  • Ardakan, Mostafa Abouei

Abstract

Improving system reliability without increasing system cost or weight is a realm of great attraction for system designers. This objective can be achieved by developing new redundancy strategies that improve system reliability by changing the activation time of redundant components. In this paper, a new unified redundancy strategy called “G-mixed†is introduced. The G-mixed strategy is a general form of previous redundancy strategies, which can be converted to all other forms. In this strategy, the number of components that have to be kept in active mode is considered as a decision variable and optimized by a mathematical model. The efficiency of the proposed strategy is investigated in different problem instances. Results indicate that, in most cases, the new G-mixed strategy outperforms the previously reported ones including the K-mixed, mixed, standby, and active counterparts. Another aspect of the study involves determining the superiority of different strategies under different combinations of component and switch reliabilities. It is found that switch unreliability has the least effect on the efficiency of the proposed strategy when compared with those that require a switching system.

Suggested Citation

  • Sedaghat, Niloofar & Ardakan, Mostafa Abouei, 2021. "G-mixed: A new strategy for redundant components in reliability optimization problems," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004403
    DOI: 10.1016/j.ress.2021.107924
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    References listed on IDEAS

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    12. 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).
    13. Chunyan Ling & Jingzhe Lei & Way Kuo, 2024. "A sequential two-stage approach based on variational Bayesian inference for reliability-redundancy allocation," Journal of Risk and Reliability, , vol. 238(1), pages 136-157, February.
    14. Hsieh, Tsung-Jung, 2023. "A Q-learning guided search for developing a hybrid of mixed redundancy strategies to improve system reliability," Reliability Engineering and System Safety, Elsevier, vol. 236(C).

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