항공안전데이터 활용 이상징후 분석을 통한 안전관리 개선방안 도출

Abstract

With the recent decline in the momentum of COVID-19, aircraft operations are showing a recovery trend, resulting in a number of large and small safety events. On September 22, 2022, a South Korea airline collided with another plane landing while preparing for takeoff at Heathrow Airport in London, and on October 23, 2022, a South Korea airplane left the runway while landing at the Philippines’ Cebu Maktan Airport, severely damaging its fuselage and causing passengers and crew to escape. A week later, a South Korea airplane leaving Incheon International Airport for Sydney, Australia, returned to Incheon International Airport due to engine problems shortly after takeoff. In order to prepare for aviation safety events leading to major accidents and implement proactive and effective safety management to respond appropriately to the changing environment, it is necessary to seek new methods, not existing safety management methods. This paper analyzes recent aviation safety issues and overseas safety management cases using aviation data, and presents measures to detect, analyze, and utilize abnormal symptoms through data. It is suggested that a data-based safety management system should be prepared in order to predict abnormalities in advance and efficiently manage events occurring in the future.