Invitation to public dissertation defense at Engineering Management and Systems Engineering
<p> ANNOUNCEMENT OF PUBLIC DEFENSE OF A DOCTOR OF PHILOSOPHY</p> <p> </p> <p> Title: THE RELATIONSHIP AMONG HFACS LEVELS and ANALYSIS of HUMAN FACTORS in UNMANNED and MANNED AIR VEHICLES</p> <p> By: Veysel Yesilbas, a doctor of philosophy candidate in the Department of Engineering Management and Systems Engineering</p> <p> When: Thursday, April 17, 2014 at 10:00 a.m.</p> <p> Where: Kaufman Hall 239</p> <p> ABSTRACT</p> <p> Accident investigation and evaluation has been an important part of military and commercial aviation since its beginning. Investigators and researchers seek to understand the root causes leading to accidents, exploit the reasons behind root causes, and improve flight safety by presenting safety recommendations that can be used by other researchers, educators, managers of airline or military organizations, and aircraft manufacturers.</p> <p> Among aviation accident investigation tools, the Human Factors Analysis and Classification System (HFACS) has been used by the United States Department of Defense (DOD) since 2005 as well as by commercial aviation sectors and countries worldwide. The taxonomy of HFACS has been used not only in aviation domain but also studied for its application to accident investigation in different sectors such as maritime shipping, mining and commercial traffic. While the need for humans in operating environment is decreasing, the expectation for human performance quality in aviation and industrial sectors is increasing.</p> <p> This research applies a quantitative ex post facto approach to test the relationship among the HFACS taxonomy levels using data from 347 U.S. Air Force Accident Investigation Board (AIB) reports between the fiscal years of 2000 and 2013. This research analyzes the structure of causal paths among HFACS levels by applying the structural equation modeling methodology and then compares the common significant paths between unmanned and manned air vehicle accident causes by applying path analysis for unmanned and manned accidents. The study found the presence of statistically significant paths at both UAV and MAV accidents and common partial paths of those aircraft types within the framework of DOD HFACS taxonomy. The study also suggests that accident data can be utilize to develop, test, and improve the failure model of an organization to promote understanding of any significant effect such as technology and structural changes in the organization.</p>
Posted By: Steven Cotter
Date: Fri Apr 04 09:46:36 EDT 2014