Abstract
As revealed by the mishap causal factor statistics, human errors pose more threats to the safe operation of Unmanned Aerial System (UAS). Moreover, the number of human error induced maintenance accident has risen to a comparable level as the accidents due to flight crew error, but little prior research on the causality analysis can be found, especially consider the organizational context of human performance shaping factors. Based on the System Dynamics approach, this study proposed hierarchical risk archetypes that model the interactions of organizational, human and physical system factors leading to maintenance accident of large UASs. The archetypes help to clarify why technical reliability improvement measures, career training and accident investigation always fail to gain expected safety benefits. As organizational risk assessment tools, more detailed quantitative SD model can be developed based on those archetypes to evaluate potential safety policy and management decisions in the field of large UAS maintenance.
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Acknowledgments
This research was sponsored by the National Science Foundation of China (No. 61803263). The first author also thanks Professor Karen B Marais for helpful advice during the process of this research.
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Lu, Y., Huangfu, H., Zhang, S., Fu, S. (2020). Organizational Risk Dynamics Archetypes for Unmanned Aerial System Maintenance and Human Error Shaping Factors. In: Boring, R. (eds) Advances in Human Error, Reliability, Resilience, and Performance. AHFE 2019. Advances in Intelligent Systems and Computing, vol 956. Springer, Cham. https://doi.org/10.1007/978-3-030-20037-4_7
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DOI: https://doi.org/10.1007/978-3-030-20037-4_7
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