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How reliable should military UAVs be?

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  • Qingqing Zhai
  • Zhi-Sheng Ye

Abstract

The recent decade has witnessed an emerging usage of Unmanned Aerial Vehicles (UAVs) in both military and civilian applications. Compared with manned aircraft, a much larger percentage of UAVs are reported to crash every year, due to its unmanned nature and immature technologies. The high failure rate is mainly attributed to the lack of redundancy design and insufficient reliability growth tests. It is natural to ask whether the UAVs are reliable enough, and to what extent we shall improve the reliability of the UAVs. Through cost modeling, this study shows that the designed reliability for military UAVs needs not be extremely high. The main reason is that military UAVs are exposed to external threats such as enemy fire and cyber-attacks. Reliability enhancement actions are able to improve the operational reliability, but cannot ease the external threats to the UAVs. In our UAV cost models, both the reliability enhancement actions using reliability growth test and external failures due to intentional attacks are considered, based on which the optimal reliability growth duration that minimizes the total operation cost is derived. We investigate the impacts of the reliability growth pattern and the intensity of external threats on the effectiveness of the reliability growth test. Particularly, the external threats can weaken the effectiveness of the reliability growth test in terms of the overall operation cost. An illustrative example is used to demonstrate our model and support our results.

Suggested Citation

  • Qingqing Zhai & Zhi-Sheng Ye, 2020. "How reliable should military UAVs be?," IISE Transactions, Taylor & Francis Journals, vol. 52(11), pages 1234-1245, November.
    • Handle: RePEc:taf:uiiexx:v:52:y:2020:i:11:p:1234-1245
    DOI: 10.1080/24725854.2019.1699977
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    Cited by:

    1. Zhao, Xian & Lv, Zuheng & Qiu, Qingan & Wu, Yaguang, 2023. "Designing two-level rescue depot location and dynamic rescue policies for unmanned vehicles," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    2. 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).
    3. Adam Bondyra & Marek Kołodziejczak & Radosław Kulikowski & Wojciech Giernacki, 2022. "An Acoustic Fault Detection and Isolation System for Multirotor UAV," Energies, MDPI, vol. 15(11), pages 1-19, May.

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