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This paper describes a safety information management system designed to capture maintenance factors that contribute to aircraft mishaps. The Human Factors Analysis and Classification System-Maintenance Extension (HFACS-ME), an effective framework for classifying and analyzing maintenance errors that lead to mishaps, incidents, and personal injuries, is the theoretical foundation. An existing desktop mishap application is updated, a prototype web-based model is developed, and an Asynchronous Distributed Learning (ADL) module is conceptualized. These tools facilitate data collection, organization, query, analysis, and the reporting of maintenance errors that contribute to aviation mishaps. Together they represent a complete, robust system for analyzing aircraft maintenance mishap related factors anywhere at anytime.

The SPA-10 project, sponsored by U.S. National Science Foundation, is to acquire and qualify a replacement for the retired T-28 “storm penetration” aircraft previously used to acquire meteorological data to enable understanding and modelling of mid-continent thunderstorms. The National Science Foundation selected the Fairchild A-10 (bailed from the U.S. Air Force) as the platform to be adapted to perform the storm penetration mission to altitudes of eleven kilometers, and funded Naval Postgraduate School’s Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) as prime contractor. An expert panel conducted a review of the SPA-10 project in 2014 and recommended a risk analysis addressing hazards to the aircraft and pilots, such as icing, hail, turbulence and lightning. This paper presents the results of the risk analysis performed in response to this need, including recommended mitigations.

The paper considers an approach for improvement of the safety of landing operations through the development and implementation of LCD-based display, integrating all necessary information and providing it to a pilot in the most convenient, cognitive and relevant form. This information includes both a set of traditional gauges with all relevant constraints optimized in form, place, and color from a pilots’ standpoint, and the outputs from a perspective system supporting pilot’s control actions, providing continuous cognitive prompt in the view of recommended near-optimal road-in-the-sky (calculated for the current conditions in real time). The paper describes general ideas of a proposed integrated indicator and explains its images and symbols. It also includes the results of this indicator testing on a specialized simulator and in a real flight on board a transport aircraft Antonov-72.