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Reliability modeling for balanced systems considering mission abort policies

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  • Fang, Chen
  • Chen, Jianhui
  • Qiu, Daizhen

Abstract

This paper studies a mission abort policy to avoid the high probability of system failure for a balanced system performing a specific mission continuously over a period of time. The system comprises two subsystems with multiple states, and a balance criterion proposed in this paper is based on the state distance between the two subsystems. A mission abort policy is implemented when the system enters into unbalanced subsets reaching a limited number of times. The system is considered to have failed if one of the subsystems enters into an absorbing state. To assess the system's performance, two probability indices, namely mission success probability and system survivability, are derived by using the theory of aggregated stochastic processes. To validate the findings presented in this paper, a case study involving an unmanned aerial vehicle performing a mission is conducted. The results of this case study effectively demonstrate the efficacy of the proposed mission abort policy and the derived probability indices.

Suggested Citation

  • Fang, Chen & Chen, Jianhui & Qiu, Daizhen, 2024. "Reliability modeling for balanced systems considering mission abort policies," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:reensy:v:243:y:2024:i:c:s0951832023007676
    DOI: 10.1016/j.ress.2023.109853
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    References listed on IDEAS

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    1. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2022. "Mission aborting and system rescue for multi-state systems with arbitrary structure," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    2. Fang, Chen & Cui, Lirong, 2021. "Reliability evaluation for balanced systems with auto-balancing mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
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    4. Peng, Rui, 2018. "Joint routing and aborting optimization of cooperative unmanned aerial vehicles," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 131-137.
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    6. Zhao, Xian & Fan, Yu & Qiu, Qingan & Chen, Ke, 2021. "Multi-criteria mission abort policy for systems subject to two-stage degradation process," European Journal of Operational Research, Elsevier, vol. 295(1), pages 233-245.
    7. Zhao, Xian & Liu, Haoran & Wu, Yaguang & Qiu, Qingan, 2023. "Joint optimization of mission abort and system structure considering dynamic tasks," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    8. Zhao, Xian & Dai, Ying & Qiu, Qingan & Wu, Yaguang, 2022. "Joint optimization of mission aborts and allocation of standby components considering mission loss," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    9. Liu, Lujie & Yang, Jun, 2023. "A dynamic mission abort policy for the swarm executing missions and its solution method by tailored deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
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    Cited by:

    1. Meng, Sa & Xing, Liudong & Levitin, Gregory, 2024. "Activation delay and aborting policy minimizing expected losses in consecutive attempts having cumulative effect on mission success," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    2. Zhao, Xian & Han, He & Jiao, Chunhui & Qiu, Qingan, 2024. "Reliability modeling of k-out-of-n: F balanced systems with common bus performance sharing," Reliability Engineering and System Safety, Elsevier, vol. 248(C).

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