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Airport Facility Tech Trends

With borders easing on travel controls and tourism beginning to kickstart 2022, more and more airports are embracing new trends and innovations to welcome a post-pandemic generation of travelers. 2022 will be a year the features increasing automation and usage of biometrics According to the Port of Seattle website, here are a few of them:


Machine Learning


Machine learning is a subset of artificial intelligence (AI) that allows software to become more accurate at predicting outcomes based on data points and trends, without the operator having to directly instruct the software to do so.


Seattle Airport’s surface area management system uses computer vision technology to monitor ground handling and servicing activity around any aircraft parked at a gate. Computer vision technology has also been applied to monitor activity at cargo bays which are holding areas for larger-sized cargo planes.


Machine learning is also employed with sound or acoustic sensors to determine whether an aircraft is using its auxiliary power unit (APU), which emits CO2 gases and other emissions.



Biometric facial recognition


The COVID-19 pandemic was a driver for innovation with limited evaluation or compelling business cases. Airport facilities were confronted with an unprecedented demand for health-related ideas that could be implemented quickly.


One of the most successful ideas from the pandemic era was the use of biometric facial recognition technology to create a “touchless” passenger experience. For example, this year Seattle Airports implemented a biometric air exit (BAX) solution designed by Customs and Border Protection (CBP). BAX is a touchless (therefore safer and more hygienic) solution used by our airline partners to process passengers prior to departure.



Autonomous vehicles


An easier problem to solve is autonomous driving on the airport’s tarmac or bus routes between airport facilities. Several airports in both Europe and the U.S. conducted trials to determine the obstacles and benefits of autonomous vehicles at airports.


  • Heathrow Airport — Autonomous electric tugs automated aircraft taxiing, reducing pushback-related delays by 53 percent

  • Fagernes Airport — Autonomous snow removal equipment cleared 357,500 square meters of snow in an hour, reducing costs, emissions, and delays

  • Dallas Fort Worth International Airport — Autonomous luggage carts handled 450 bags per hour, using half the energy of conventional baggage handling systems

  • Seattle-Tacoma International Airport — A proof of concept of an interline autonomous baggage cart is underway

 
 
 

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Course Overview

Where traditional maintenance management programs rely on routine servicing of all machinery and fast response to unexpected failures, a predictive maintenance program schedules specific maintenance tasks as they are actually preventing and extending equipment life usefulness.
 

To understand a predictive maintenance management program, traditional management techniques should first be considered in order to understand machine failures

When a machine breaks down, fix it. The “If it ain’t broke, don’t fix it” method of maintaining plant machinery has been a major part of plant maintenance operations.

Course Objectives

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Also, for those who are in operations would like to acquire an understanding of how the quality of the maintenance activities affects their equipment functions if wrong type of elements used.

 

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​Module 1: Objectives of Equipment Maintenance
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