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A novel component mixing and mixed redundancy strategy for reliability optimization

Author

Listed:
  • Saeideh Sheikhpour

    (Shahid Bahonar University of Kerman)

  • Amin Kargar-Barzi

    (Shahid Bahonar University of Kerman)

  • Ali Mahani

    (Shahid Bahonar University of Kerman)

Abstract

Maximizing overall system reliability by identifying optimal system configuration considering several design constraints is known as reliability redundancy allocation problem (RRAP). Since reliability is an important quality attribute in critical systems, RRAP has been intensively investigated in the literature. In this paper, a new model of RRAP for heterogeneous and homogeneous components is developed. Our proposed model handles component mixing in subsystems under both active and cold-standby redundancy strategies. The problem, therefore, is to decide the number of components in each subsystem (redundancy level), the failure rate of selected components, and the type of redundancy strategy for each of them under multiple design constraints including system weight, cost, and volume. Since RRAP falls into the NP-hard category of engineering optimization problems, a teaching learning-based optimization (TLBO) algorithm is implemented to solve it. Finally, the simulation results of the proposed RRAP model by TLBO on three well-known benchmark problems are provided, followed by the comparisons with recent existing related works. The comparative results suggested the effectiveness of the proposed approach in finding the optimal system configuration with higher system reliability in all cases.

Suggested Citation

  • Saeideh Sheikhpour & Amin Kargar-Barzi & Ali Mahani, 2022. "A novel component mixing and mixed redundancy strategy for reliability optimization," 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. 13(1), pages 328-346, February.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01248-y
    DOI: 10.1007/s13198-021-01248-y
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    References listed on IDEAS

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    1. Kim, Heungseob & Kim, Pansoo, 2017. "Reliability models for a nonrepairable system with heterogeneous components having a phase-type time-to-failure distribution," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 37-46.
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    4. 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.
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    6. Mostafa Abouei Ardakan & Mohammad Sima & Ali Zeinal Hamadani & David W. Coit, 2016. "A novel strategy for redundant components in reliability--redundancy allocation problems," IISE Transactions, Taylor & Francis Journals, vol. 48(11), pages 1043-1057, November.
    7. 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.
    8. Dolatshahi-Zand, Ali & Khalili-Damghani, Kaveh, 2015. "Design of SCADA water resource management control center by a bi-objective redundancy allocation problem and particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 11-21.
    9. 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.
    10. Dobani, Ehsan Ramezani & Ardakan, Mostafa Abouei & Davari-Ardakani, Hamed & Juybari, Mohammad N., 2019. "RRAP-CM: A new reliability-redundancy allocation problem with heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    11. Gianpaolo Di Bona & Antonio Forcina & Domenico Falcone & Luca Silvestri, 2020. "Critical Risks Method (CRM): A New Safety Allocation Approach for a Critical Infrastructure," Sustainability, MDPI, vol. 12(12), pages 1-19, June.
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    Cited by:

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    2. 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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