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Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies: Erlang time-to-failure distribution

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  • Meisam Sadeghi
  • Emad Roghanian

Abstract

This article deals with a new redundancy allocation model for non-repairable series-parallel systems with multiple strategy choices. The proposed model simultaneously determines the type of components, number of active and standby components to maximize system reliability subject to design constraints. Traditionally, due to complexity and difficulty in obtaining the closed form version of system reliability, a convenient lower-bound on system reliability has been widely applied to approximate it. Assuming that switching mechanism time-to-failure is exponentially distributed, the closed form version of the reliability of subsystems with cold standby redundancy is derived analytically for the first time. This is successfully performed using Markov process and solving the relevant set of differential-difference equations. With respect to the obtained formulation, a semi-analytical expression for the reliability of subsystems with mixed redundancy strategy is also extracted. Component time-to-failure is assumed to follow an Erlang distribution which is suitable for most engineering design problems. The presented model is linear and in the form of standard zero-one integer programs and thus using integer programming algorithms guarantees optimal solutions. The computational results of solving a well-known example indicate the high performance of the proposed model in improving system reliability.

Suggested Citation

  • Meisam Sadeghi & Emad Roghanian, 2017. "Reliability optimization for non-repairable series-parallel systems with a choice of redundancy strategies: Erlang time-to-failure distribution," Journal of Risk and Reliability, , vol. 231(5), pages 587-604, October.
  • Handle: RePEc:sae:risrel:v:231:y:2017:i:5:p:587-604
    DOI: 10.1177/1748006X17717615
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    References listed on IDEAS

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    1. Kong, Xiangyong & Gao, Liqun & Ouyang, Haibin & Li, Steven, 2015. "Solving the redundancy allocation problem with multiple strategy choices using a new simplified particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 147-158.
    2. 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.
    3. Nahas, Nabil & Nourelfath, Mustapha & Ait-Kadi, Daoud, 2007. "Coupling ant colony and the degraded ceiling algorithm for the redundancy allocation problem of series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 92(2), pages 211-222.
    4. Liang, Yun-Chia & Chen, Yi-Ching, 2007. "Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm," Reliability Engineering and System Safety, Elsevier, vol. 92(3), pages 323-331.
    5. Abouei Ardakan, Mostafa & Zeinal Hamadani, Ali, 2014. "Reliability optimization of series–parallel systems with mixed redundancy strategy in subsystems," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 132-139.
    6. Rui Peng & Qingqinq Zhai & Liudong Xing & Jun Yang, 2016. "Reliability analysis and optimal structure of series-parallel phased-mission systems subject to fault-level coverage," IISE Transactions, Taylor & Francis Journals, vol. 48(8), pages 736-746, August.
    7. 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.
    8. 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.
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    Cited by:

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