Flight Training Risk Identification and Assessment Based on the HHM-RFRM Model

Hong Sun, Fangquan Yang, Peiwen Zhang () and Yunxiang Zhao
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Hong Sun: Flight Technology and Flight Safety Research Base, Civil Aviation Flight University of China, Guanghan 618307, China
Fangquan Yang: School of Airport, Civil Aviation Flight University of China, Guanghan 618307, China
Peiwen Zhang: School of Economics and Management, Civil Aviation Flight University of China, Guanghan 618307, China
Yunxiang Zhao: Flight Training Standards Branch, Civil Aviation Flight University of China, Guanghan 618307, China

Sustainability, 2023, vol. 15, issue 2, 1-20

Abstract: Due to the unavoidable operational risks and insufficient risk management capabilities of beginner pilots in flight training, the challenge of risk control in aviation schools has become increasingly prominent. To ensure the safety of flight training in aviation schools and to reduce costs and increase revenue, the essential prerequisite for improving efficiency is risk management. Therefore, it is necessary to explore risk identification and assessment methods. This paper adopts the holographic modeling (HHM) method and risk filtering, rating and management (RFRM) theory. First, the HHM idea is used to construct a risk identification framework (HHM-PAVE) for flight training. Second, based on the dual criteria, multiple criteria and cloud model (CM) in the RFRM approach, an improved risk assessment matrix-cloud model (IPC-CM) is proposed and combined with the N-K model and Bayes’ theorem to propose a coupled risk scenario hazard measurement model (CR-HM) based on the HHM-RFRM approach in risk assessment. In the assessment process, the impact of risk factors on system stability as well as the uncertainty problem and coupling–risk quantification problem in expert assessment are considered to obtain scientific and objective quantitative assessment results. Finally, the risk identification and assessment experiments were conducted using HHM-RFRM on the flight training. The results show that the method can more accurately identify critical risk factors in a flight training system and provide a new perspective for risk prevention and control.

Keywords: safety engineering; flight training; HHM-RFRM; risk identification; risk assessment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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