Defining means to assess safety performance and delve into their causes is one of the current and future challenges of the ATM sector. Following the experiences of the Aerospace Performance Factor by FAA and EUROCONTROL, this research aims to apply the Analytic Hierarchy Process (AHP) in order to build synthetic and user-friendly safety reactive indicators. Therefore, it describe the process for evolve these indicators to a proactive perspective, in order to forecast future safety performance. This concept has been possible through the development of a statistical model of safety events, combining in a Monte Carlo simulation the results emerged from the literature analysis with the analytical models of historic data interpretation. Through the analysis and combination of the safety events over time (accidents, incidents and issues) and the relative control charts, this model will pinpoint critical situations and will address the interventions of the decision makers.
ATM safety management: reactive and proactive indicators forecasting and monitoring ATM overall safety performance / DI GRAVIO, Giulio; Mancini, M.; Patriarca, Riccardo; Costantino, Francesco. - (2014). (Intervento presentato al convegno 4th SESAR Innovation Days (SIDs 2014) EUROCONTROL tenutosi a Madrid (Spagna) nel 25/27 novembre 2014).
ATM safety management: reactive and proactive indicators forecasting and monitoring ATM overall safety performance
DI GRAVIO, GIULIO;PATRIARCA, RICCARDO;COSTANTINO, francesco
2014
Abstract
Defining means to assess safety performance and delve into their causes is one of the current and future challenges of the ATM sector. Following the experiences of the Aerospace Performance Factor by FAA and EUROCONTROL, this research aims to apply the Analytic Hierarchy Process (AHP) in order to build synthetic and user-friendly safety reactive indicators. Therefore, it describe the process for evolve these indicators to a proactive perspective, in order to forecast future safety performance. This concept has been possible through the development of a statistical model of safety events, combining in a Monte Carlo simulation the results emerged from the literature analysis with the analytical models of historic data interpretation. Through the analysis and combination of the safety events over time (accidents, incidents and issues) and the relative control charts, this model will pinpoint critical situations and will address the interventions of the decision makers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.