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Safety Performance of Complex Systems: Lesson Learned from ATM Resilience Analysis | OMICS International | Abstract
ISSN: 2169-0316

Industrial Engineering & Management
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Research Article

Safety Performance of Complex Systems: Lesson Learned from ATM Resilience Analysis

Giulio Di Gravio* and Riccardo Patriarca

Department of Mechanical and Aerospace Engineering, University of Rome “La Sapienza”, Via Eudossiana, 18, 00184 Roma, Italy

*Corresponding Author:
Gravio GD
Department of Mechanical and Aerospace Engineering
University of Rome “La Sapienza”
Via Eudossiana
18, 00184 Roma
Tel: 339 1418420
E-mail: [email protected]

Received date: October 08, 2015; Accepted date: June 28, 2016; Published date: June 30, 2016

Citation: Gravio GD, Patriarca R (2016) Safety Performance of Complex Systems: Lesson Learned from ATM Resilience Analysis. Ind Eng Manage 5: 193. doi:10.4172/2169-0316.1000193

Copyright: © 2016 Gravio GD, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



The Air Traffic Management (ATM) system has become steadily more complex due to rampant technological, procedural and societal developments and to the increase in traffic volume. These factors have become gradually more difficult to understand and manage, mainly because of tight couplings among functions and because of the continuous development characterizing everyday activities. According to this view, traditional safety analyses, basing on the belief that the systems are completely known and a causal-effect link could ever be easily detected may become ineffective. Furthermore, these methodologies can evaluate only linear causal dependencies. It is necessary therefore to evolve ATM risk assessment from its classic view of safety (Safety-I), to a new one, integrating the principles of resilience engineering (Safety-II). This editorial article presents the complexity and the outcomes deriving from resilience engineer methodologies, aiming at illustrating possible guidelines for managers and academics.