Flightsafety Criteria to assess the safety performance of cockpit crew

Document Type : Original Article

Authors

1 University of Tehran

2 university of Tehran

10.22034/joae.2023.387633.1160

Abstract

Flight crew management is an important factor in flight in order to ensure operational safety and reduce flight errors. In order to monitor all threats and errors managed or not by flight pilots, considering flight safety factors that will have a direct impact on pilots' errors is one of the basic and important issues to maintain an airline at an acceptable level of safety performance. In accordance with literature review study on the subject in airline companies, it is observed that there is a gap in the comprehensive consideration of the identification and evaluation of the basic factors of flight safety which are affected on the pilot’s errors during flight. Therefore, in this paper, an evaluation method of the pilot’s performance management is proposed by providing criteria and sub-criteria and also the pilot’s error assessment in order to increase the level of flight safety. The statistical population of this research is active airline pilots in Airbus fleets of wide-body and narrow-body aircrafts. Simple random sampling has been used to collect the data which are needed for the research and also to analyze them. In this research, the method of data discovery and content validity has been used in order to identify the criteria which are affected the pilot’s error. The most important achievement of the paper are the identification of the types of errors which affecting the pilot’s error and how to evaluate them, as well as the discovery of the effective safety factors.

Keywords

Main Subjects


  •  [1]. ICAO. (2013). Safety Management Manual. Doc. 9859. In: International Civil Aviation Organization Montreal, Canada.
  • [2].Authority, C. A. (2014). Flight-crew human factors handbook. CAP, 737, 55-70.
  • [3].Wiener, E. L., Kanki, B. G., & Helmreich, R. L. (2010). Crew resource management: Academic Press.
  • [4].ICAO, D. 9803, 2002, Line Operation Safety Audit. International Civil Aviation Organization, 2022.
  • [5].Robertson, O. (2014). Gender and Crew Resource Management: A Phenomenological Qualitative Study. University of Phoenix,
  • [6]. Wiener, E. L., Kanki, B. G., & Helmreich, R. L. (2010). Crew resource management: Academic Press.
  • [8].ICAO. (2012). 9966,“. Fatigue Risk Management Systems”, Canada.
  • [9].Wang, Z., & Chen, C. (2017). Fuzzy comprehensive Bayesian network-based safety risk assessment for metro construction projects. Tunnelling and Underground Space Technology, 70, 330-342.
  • [10].Efthymiou, M., Whiston, S., O'Connell, J. F., & Brown, G. D. (2021). Flight crew evaluation of the flight time limitations regulation. Case Studies on Transport Policy, 9(1), 280-290.
  • [11].Gautam, A., & Garg, N. (2021). Impact of Perceived Stress, Safety Attitude and Flight Experience on Hazardous Event Involvement of Aviators.
  • [12]. Seah, B. Z. Q., Gan, W. H., Wong, S. H., Lim, M. A., Goh, P. H., Singh, J., & Koh, D. S. Q. (2021). Proposed data-driven approach for occupational risk management of aircrew fatigue. Safety and health at work, 12(4), 462-470.
  • [13]. Chang, Y.-H., Yang, H.-H., & Hsiao, Y.-J. (2016). Human risk factors associated with pilots in runway excursions. Accident Analysis & Prevention, 94, 227-237.
  • [14]. Grant, J. S., & Davis, L. L. (1997). Selection and use of content experts for instrument development. Research in nursing & health, 20(3), 269-274.
  • [15]. Rubio, D. M., Berg-Weger, M., Tebb, S. S., Lee, E. S., & Rauch, S. (2003). Objectifying content validity: Conducting a content validity study in social work research. Social work research, 27(2), 94-104.
  • [16].Polit, D. F., Beck, C. T., & Owen, S. V. (2007). Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Research in nursing & health, 30(4), 459-467.
  • [17].Deveci, M., & Demirel, N. C. (2018). Evolutionary algorithms for solving the airline crew pairing problem. Computers & Industrial Engineering, 115, 389-406.
  • [18]. Aydemir-Karadag, A., Dengiz, B., & Bolat, A. (2013). Crew pairing optimization based on hybrid approaches. Computers & Industrial Engineering, 65(1), 87-96.
  • [19].Kornilakis, H., & Stamatopoulos, P. (2002). Crew pairing optimization with genetic algorithms. Paper presented at the Hellenic conference on artificial intelligence.
  • [20]ICAO. (2007). International Civil Aviation Vocabulary. Doc. 9713. In: International Civil Aviation Organization Montreal, Canada.
  • [21] Pérez-Campuzano, D., Andrada, L. R., Ortega, P. M., & López-Lázaro, A. (2022). Visualizing the historical COVID-19 shock in the US airline industry: A Data Mining approach for dynamic market surveillance. Journal of Air Transport Management, 101, 102194.
  • [22]ICAO (2001). International Civil Aviation Vocabulary (Vol. 9713).
  • [23] Badánik, B., Le Duc, M., & Kandera, B. (2021). Understanding scheduling preferences of airline crews. Transportation Research Procedia, 59, 223-233.