Cross-database analysis to identify relationships between aircraft accidents and incidents.

摘要

Air transportation systems are designed to ensure that aircraft accidents are rare events. To minimize these accidents, factors causing or contributing to accidents must be understood and prevented. Despite many efforts by the aviation safety community to reduce the accidents, accident rates have been stable for decades. One explanation could be that direct and obvious causes that previously occurred with a relatively high frequency have already been addressed over the past few decades. What remains is a much more difficult challenge---identifying less obvious causes, combinations of factors that, when occurring together, may potentially lead to an accident.Contributions of this research to the aviation safety community are two-fold: (1) The analyses conducted in this research, identified significant accident factors. Detection and prevention of these factors, could prevent potential future accidents. The holistic study made it possible to compare the factors in a common framework. The identified factors were compared and ranked in terms of their likelihood of being involved in accidents. Corrective actions by the FAA Aviation Safety Oversight (ASO), air carrier safety offices, and the aviation safety community in general, could target the high-ranked factors first. The aviation safety community can also use the identified factors as a benchmark to measure and compare safety levels in different periods and/or at different regions. (2) The methodology established in this study, can be used by researchers in future studies. By applying this methodology to the safety data, areas prone to future accidents can be detected and addressed. Air carriers can apply this methodology to analyze their proprietary data and find detailed safety factors specific to their operations. The Factor Support Ratio metric introduced in this research, can be used to measure and compare different safety factors. (Abstract shortened by UMI.)