Only 10% of airports describe their ground handling efficiency as "Excellent".* With multiple stakeholders and up to 80 vehicles around an aircraft such as an A380, and 200 steps in the wheels down process, there is extreme pressure on ground handlers to achieve turnaround within minutes.
Real-time optimization of ground operations is complex, with various security issues at stake. Not only are there many stakeholders to be managed, there is fierce competition regarding sharing of information especially around resource allocation.
Even a 10-minute reduction in turnaround time can improve airplane utilization by 8% and has a high impact on profitability. A smart holistic solution which integrates all data from queueing to luggage loading, that integrates with other airport systems such as the A-SMGCS would be a definite win.
ADB SAFEGATE is working towards a smart solution that improves situational awareness in real time, and optimizes movements of all vehicles and stakeholders on the ground, and thus, optimizes overall time and money spent from wheels down to wheels up. The suite will comprise three applications – real-time situational awareness information, mobile resources allocation and performance monitoring and reporting.
Our value propositions
A user can choose what aprons are to be visualized, and monitor in real-time, the work progress of each team for a given apron on a mobile device. A disruption management device recommends possible solutions to help the user take short term decisions. In case of disruptions or deviations, differentiated alerts (red/ green) are sent to stakeholders depending on estimated impact. A quick visualization of level of alert helps the user to focus actions on priority aprons.
Monitoring: The operations manager can set thresholds for Key Performance Indicators (KPIs) not only at the gate but also the airport level, monitor them in real time and get alerts in case of deviations. The tool identifies possible causes for performance issues, the significance and gravity, and suggests corrective actions.
Reporting: The operations manager can use filters to generate fully customizable reports based on historical data and identify possible root causes for issues. In addition, the tool uses machine learning to compute, refine and predict standard turnaround times.
*Frost & Sullivan Digital Transformation of Airport Airside Operations
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