A risk analysis model of flight operations based on region partition

Abstract

Purpose -The purpose of this paper is to focus on flight exceedances in pilots' operations. With some bad conditions, such as a bad weather, flight exceedances might lead to serious consequences. They are significant hidden dangers of aviation. Risk analysis is carried out to identify pilots' high-risk or low-risk operations. Design/methodology/approach -A multi-objective optimization model is proposed for risk analysis of flight operations. An evolutionary algorithm is designed to divide flight operation state-space into some high-risk and low-risk sub-spaces. Findings -Through the empirical study of a certain flight exceedance with the analysis model, the authors discover some high-risk flight operations, which indicate coordination problems in coordinate control of airplane's speed, rate of descent, heading, roll and pitch, etc. Originality/value -This paper employs a quantitative model to carry out risk analysis of flight operations. The results are useful to pilots' training and may improve flight safety fundamentally. The risk analysis of flight exceedance is one specific case in airlines safety risk management. Some other problems, such as cause analysis of flight delay, aircraft faults diagnosis, can be addressed in the same way and dealt with by specific model adjustments and algorithm designs.

Abusive supervision, thwarted belongingness, and workplace safety: A group engagement perspective.

“…This system monitors and records 99 -101 parameters of flight status, depending on the plane model (e.g., Boeing 757 vs. 737-700). In the literature on aviation safety, QAR data have been widely applied to flight operation diagnostics as they can predict aircraft status and potential hazards during a flight (Hadjimichael, 2009;Shao, Qi, & Gao, 2012). In our research, errors were coded by the airline company based on the established standards described in the aircraft flight manual.…”

Risk assessment method for controlled flight into terrain of airlines based on QAR data

“…Diverse data analysis systems are developed to explore operational risks, evaluate and assess pilot flight technology, identify technical training problems, optimize training processes, enhance flight training quality, monitor flight quality, engine status and elevate the underutilized QAR data rate (Haverdings and Chan, 2010; Sun, 2003; Li, 2010). Risk assessment model of aircraft performance (Wang et al , 2019b), aircraft performance prediction model (Tong et al , 2018), flight dynamic model (Höhndorf et al , 2017), fuel consumption model of the climbing phase of departure aircraft (Huang et al , 2019), risk analysis model of flight operation (Shao et al , 2012; Wang et al , 2014) and aircraft performance mode (Hernández Herrera, 2018) are constructed to evaluate aircraft performance and operation risk, identify critical links of flight operation and high-risk operations, analyze pilot’s operation behavior, mitigate aircraft accidents and improve flight management efficiency.…”

“…Risk assessment model of aircraft performance (Wang et al , 2019b), aircraft performance prediction model (Tong et al , 2018), flight dynamic model (Höhndorf et al , 2017), fuel consumption model of the climbing phase of departure aircraft (Huang et al , 2019), risk analysis model of flight operation (Shao et al , 2012; Wang et al , 2014) and aircraft performance mode (Hernández Herrera, 2018) are constructed to evaluate aircraft performance and operation risk, identify critical links of flight operation and high-risk operations, analyze pilot’s operation behavior, mitigate aircraft accidents and improve flight management efficiency.…”