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http://dx.doi.org/10.36498/kbigdt.2020.5.1.181

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

Park, Shin-nyum (포항공과대학교 산업경영공학과)
Song, Minseok (포항공과대학교 산업경영공학과)
Publication Information
The Journal of Bigdata / v.5, no.1, 2020 , pp. 181-188 More about this Journal
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.
Keywords
Baggage Handling System(BHS); Process Mining; Logistics Simulation; Machine Learning;
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