The Journal of Bigdata (한국빅데이터학회지)

Korea Bigdata Society (한국빅데이터학회)
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A Process Perspective Event-log Analysis Method for Airport BHS (Baggage Handling System)

공항 수하물 처리 시스템 이벤트 로그의 프로세스 관점 분석 방안 연구

  • 박신념 (포항공과대학교 산업경영공학과) ;
  • 송민석 (포항공과대학교 산업경영공학과)
  • Received : 2020.08.05
  • Accepted : 2020.08.25
  • Published : 2020.08.30
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Abstract

As the size of the airport terminal grows in line with the rapid growth of aviation passengers, the advanced baggage handling system that combines various data technologies has become an essential element in order to handle the baggage carried by passengers swiftly and accurately. Therefore, this study introduces the method of analyzing the baggage handling capacity of domestic airports through the latest data analysis methodology from the process point of view to advance the operation of the airport BHS and the main points based on event log data. By presenting an accurate load prediction method, it can lead to advanced BHS operation strategies in the future, such as the preemptive arrangement of resources and optimization of flight-carrousel scheduling. The data used in the analysis utilized the APIs that can be obtained by searching for "Korea Airports Corporation" in the public data portal. As a result of applying the method to the domestic airport BHS simulation model, it was possible to confirm a high level of predictive performance.

급증하는 항공 여객의 성장세에 맞춰 여객 터미널의 규모가 대형화됨에 따라 출발, 도착, 환승 여객들이 소지한 수하물을 최단 시간 내에 신속, 정확하게 처리할 수 있는 다양한 데이터 기술들이 접목된 첨단 수하물 처리시스템(Baggage Handling System; 이하 BHS)이 필수 요소가 되었다. 따라서 본 연구에서는 공항 수하물 처리시스템 운영의 고도화를 위해, 프로세스 관점의 데이터 분석 방법론을 통한 국내 공항의 수하물 처리능력 분석 방법을 소개하고, 이벤트 로그 기반 주요 지점의 정확한 부하예측 방법을 제시하여, 자원의 선제적 배치 및 flight-carrocel 스케줄링 최적화 문제 등 향후 첨단화된 BHS 운영 전략으로 이어질 수 있도록 한다. 분석에 사용된 데이터는 공공데이터 포털에서 얻을 수 있는 '전국 공항 수송실적', '항공기 운항 정보' API를 활용하였다. 국내 공항 BHS 시뮬레이션 모델에 해당 방법을 적용한 결과, 높은 수준의 예측성능을 확인 할 수 있었다.

Keywords

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