Development of Training for New Air Traffic Control Technology Implementation

Caitlin A. Surakitbanharn, Steven J. Landry, Jittra Rukijkanpanich

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A southeast Asian air traffic control system will be undergoing a large procedural change in the next year, moving from paper flights strips to a stripless flight management system. This is the largest technological change the company has undergone in recent history, and they expressed desire to develop a training program, and this research works to identify topics to for training to directly address the concerns and needs of staff members to help ensure a smoother transition period. Open-ended questionnaires are utilized to evaluate what thoughts, concerns, and attitudes staff members have for their current system and procedures as well as their feelings towards the proposed stripless flight management system. Lexical analysis is applied to the questionnaire results to determine which topics staff members most frequently mention. The ten most frequently used words throughout the questionnaires are training/practice, equipment, easy, traffic, knowledge, compatibility, reliability, coordination, staff, and radar. These results are then used as criteria for analysis using the analytical hierarchy process (AHP), where staff members are presented with a survey to rank which criteria are most important, relative to the other criteria, in helping them perform their job tasks safely. The AHP surveys, which are still pending, are analyzed to assign a weight to each criterion, therefore mathematically assigning importance. The criteria chosen as most important by the experts (controllers and staff members) will be utilized as key points in the development of the training program for the new stripless system. A smoother training and transition period for the new system is expected by directly addressing the staff members’ thoughts and concerns up front as found through the questionnaires and AHP analysis.

Original languageEnglish (US)
Pages (from-to)2738-2745
Number of pages8
JournalProcedia Manufacturing
Volume3
DOIs
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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