Journal of Safety and Environment

To effectively identify and manage performance changes and propagation within the civil aviation operation system, this paper employs the functional resonance model to analyze the task flow involved in aircraft departure procedures. Utilizing the hierarchical task analysis method, we decompose the task flow based on the organization of the air transport system and the interactions among different entities. A total of 20 functional modules have been identified, including cockpit preparation(F₁), ATC clearance(F₂), push back request(F₃), push back permit(F₄), push back(F₅), ground traction(F₆), startup request(F₇), and startup permit(F₈), among others. It is important to note that this paper employs blind number theory to estimate the probability distribution of the 20 functional modules concerning changes in time and accuracy. This approach mitigates bias introduced by expert subjectivity. Additionally, this paper abstracts the ability of each functional module to return to a normal state when it confronted with internal and/or external perturbations into a resilience factor. This resilience factor is then used to calculate the variability of each functional module. Finally, the functional coupling value is calculated using the risk coupling formula, enabling the quantification of upstream and downstream functional interactions. This approach identifies key functions and paths that are susceptible to change and formulates risk control measures for managing performance variations. The results indicate that seven functional modules-takeoff request(F₁₄), receipt of aircraft(F₁₅), hand over from tower to approach control(F₂₀), hand over from ramp to tower control(F₁₃), takeoff(F₁₈), instructing aircraft to enter the runway(F₁₆), and takeoff permit(F₁₇)-exhibit greater variability during the aircraft departure process.Ground taxiing(F₁₂)-takeoff request(F₁₄)-takeoff permit(F₁₇)-takeoff(F₁₈)-airbone(F₁₉)-hand over from tower to approach control(F₂₀) and other two key paths are identified. When the system encounters disturbance, these functional modules are more likely to resonate with connected function modules, thereby highlighting potential failure nodes and critical paths within the process is valuable for operation analysis.