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The mishap statistics of large military unmanned aerial systems (UAS) reveal that human errors and organizational flaws pose great threats to their operation safety, especially considering the future application of derived civilian types. Moreover, maintenance accidents due to human factors have reached a significant level, but have received little attention in the existing research. To ensure the safety and sustainability of large UAS, we propose a system dynamics approach to model the maintenance risk mechanisms involving organizational, human, and technical factors, which made a breakthrough in the traditional event-chain static analysis method. Using the United States Air Force (USAF) MQ-1 Predator fleet case, the derived time-domain simulation represented the risk evolution process of the past two decades and verified the rationality of the proposed model. It was identified that the effects of maintainer human factors on the accident rate exceeded those of the technical systems in a long-term view, even though the technical reliability improvements had obvious initial effects on risk reduction. The characteristics of maintainer errors should be considered in system and maintenance procedure design to prevent them in a proactive way. It is also shown that the approach-derived SD model can be developed into a semi-quantitative decision-making support tool for improving the safety of large UAS in a risk-based view of airworthiness.

Ensuring the Safety Sustainability of Large UAS: Learning from the Maintenance Risk Dynamics of USAF MQ-1 Predator Fleet in Last Two Decades