THE USE OF AIRPORT COLLABORATIVE DECISION MAKING AND THE INDICATORS OF VARIATION OF TARGET OFF-BLOCK TIME, TARGET START-UP APPROVAL TIME AND SEQUENCE START, IN DECOLAGES AT GUARULHOS INTERNATIONAL AIRPORT

• DOI: https://doi.org/10.22533/at.ed.2164242426111

• Palavras-chave: A-CDM. Indicators. Airlines. Guarulhos.

• Keywords: A-CDM. Indicators. Airlines. Guarulhos.

• Abstract:

  
  Airport Collaborative Decision Making (A-CDM) is aimed at collaboration between airport partners on the quality and efficiency of flight information. The implementation of A-CDM at XYZ Airlines in Guarulhos is an advance in airport management, transforming the decision-making environment on the performance of take-off flights on three indicators: Target Off-Block Time (TOBT), Target Start-Up Approval Time (TSAT) and Sequence Start (SS). Thus, the problem of this research is summarized in the following question-problem: How does the A-CDM system, by estimating the TOBT, TSAT and SS metrics, show the efficiency of take-offs at XYZ Airline at Guarulhos International Airport in 2023? From this perspective, the general objective is to analyze the implementation of the A-CDM operational concept and its impact on the operational efficiency of take-offs at XYZ Airline at Guarulhos International Airport in 2023, focusing on take-offs in relation to variations in TOBT, TSAT and SS. The methodology in terms of objectives is considered descriptive. The technical procedures are bibliographical, documentary and case study. With regard to the research problem, the approach was qualitative. The analysis showed variations in the TOBT, TSAT and SS indicators in 2023.  The integration of real-time systems standardized communication with operational efficiency, punctuality and flight safety. The result showed that with A-CDM the TOBT indicator varied from 43.8% in May to 80.37% in December, reflecting problems with the season and operations at the end of the year. TSAT ranged from 1.52 in May to 5.85 in February, indicating problems with departure approvals caused by changes in demand and airport coordination. SS varied from 47.1% in January to 42.3% in October, indicating changes in allocation policies and operations.