Analysis of Aviation Safety Reporting System Incident Data Associated With the Technical Challenges of the Vehicle Systems Safety Technology Project

This analysis was conducted to support the Vehicle Systems Safety Technology (VSST) Project of the Aviation Safety Program (AVsP) milestone VSST4.2.1.01, "Identification of VSST-Related Trends." In particular, this is a review of incident data from the NASA Aviation Safety Reporting System (ASRS). The following three VSST-related technical challenges (TCs) were the focus of the incidents searched in the ASRS database: (1) Vechicle health assurance, (2) Effective crew-system interactions and decisions in all conditions; and (3) Aircraft loss of control prevention, mitigation, and recovery

Analysis of Aviation Safety Reporting System Incident Data Associated with the Technical Challenges of the Atmospheric Environment Safety Technology Project

This study analyzed aircraft incidents in the NASA Aviation Safety Reporting System (ASRS) that apply to two of the three technical challenges (TCs) in NASA's Aviation Safety Program's Atmospheric Environment Safety Technology Project. The aircraft incidents are related to airframe icing and atmospheric hazards TCs. The study reviewed incidents that listed their primary problem as weather or environment-nonweather between 1994 and 2011 for aircraft defined by Federal Aviation Regulations (FAR) Parts 121, 135, and 91. The study investigated the phases of flight, a variety of anomalies, flight conditions, and incidents by FAR part, along with other categories. The first part of the analysis focused on airframe-icing-related incidents and found 275 incidents out of 3526 weather-related incidents over the 18-yr period. The second portion of the study focused on atmospheric hazards and found 4647 incidents over the same time period. Atmospheric hazards-related incidents included a range of conditions from clear air turbulence and wake vortex, to controlled flight toward terrain, ground encounters, and incursions

capacity planning methodology for aerospace parts manufacturing in a high-mix, low volume environment

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Page 99 blank. Cataloged from PDF version of thesis.Includes bibliographical references (p. 97-98).A static capacity planning model was developed and tested following a four-phased framework. This model was developed for the purposes of capital planning for capacity requirements at a large aerospace parts manufacturing plant. Implications for capacity planning of the nature of the aerospace industry, as well as the company and plant being studied are discussed, as well as the current state of capacity planning. In phase I of model development, an appropriate modeling solution is selected. In phase II, information is collected from the user base as to the desired user experience and functionality of the model, as well as the parameters that should be considered in it. Phase III involves assessment of the parameters' impact on capacity, and identification of appropriate data sources to feed the model. Additionally, phase III recommends changes to current data structures in order to optimize the balance of model accuracy with minimal incremental resource allocation. In phase IV, the mathematical model is explained, and the user interface is developed. With a working model, the results are validated with the shop floor, identifying gaps in data sources previously unobservable. Following model development and validation, the model is applied to a subset of the shop, and used to develop recommendations for addressing predicted future capacity constraints. Application of the model reveals a blind spot in current heuristics-based planning, where high development loads can lead to immediate capacity constraints, but effects of the experience curve can actually cause this constraint to disappear on its own, without the need for excess equipment purchases. Finally, extensions of the research and lessons learned are discussed, suggesting future project work within the plant studied, as well as elsewhere in the company and in other companies or plants.by Matthew A. Reveley.S.M.M.B.A

Noosphere rising: Internet-based collective intelligence, creative labour, and social production

Our article relocates the debate about creative labour to the terrain of peer-to-peer interneting as the paradigmatic form of nonmarket - social - production. From Yann Moulier Boutang we take the point that creative labour is immaterial; it is expressed through people connected by the internet. Drawing on two social systems thinkers, Francis Heylighen and Wolfgang Hofkirchner, we transpose this connectedness up to a conception of creative labour as a supra-individual collective intelligence. This intelligence, we argue, is one of the internets emergent properties. We then present a model of internet development that flags the potential of digitally-evoked collective intelligence to facilitate what the Marxist philosopher George Caffentzis calls postcapitalist commoning. Yoking together systems theorizing about the internet and socialist envisioning of social transformation, we identify two sets of internet tools for coordination that can assist with the convivial reconstruction of society along the lines of peer-based production

Projected Impact of Compositional Verification on Current and Future Aviation Safety Risk

The projected impact of compositional verification research conducted by the National Aeronautic and Space Administration System-Wide Safety and Assurance Technologies on aviation safety risk was assessed. Software and compositional verification was described. Traditional verification techniques have two major problems: testing at the prototype stage where error discovery can be quite costly and the inability to test for all potential interactions leaving some errors undetected until used by the end user. Increasingly complex and nondeterministic aviation systems are becoming too large for these tools to check and verify. Compositional verification is a "divide and conquer" solution to addressing increasingly larger and more complex systems. A review of compositional verification research being conducted by academia, industry, and Government agencies is provided. Forty-four aviation safety risks in the Biennial NextGen Safety Issues Survey were identified that could be impacted by compositional verification and grouped into five categories: automation design; system complexity; software, flight control, or equipment failure or malfunction; new technology or operations; and verification and validation. One capability, 1 research action, 5 operational improvements, and 13 enablers within the Federal Aviation Administration Joint Planning and Development Office Integrated Work Plan that could be addressed by compositional verification were identified

An Examination of Commercial Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

The Integrated Vehicle Health Management (IVHM) Project is one of the four projects within the National Aeronautics and Space Administration's (NASA) Aviation Safety Program (AvSafe). The IVHM Project conducts research to develop validated tools and technologies for automated detection, diagnosis, and prognosis that enable mitigation of adverse events during flight. Adverse events include those that arise from system, subsystem, or component failure, faults, and malfunctions due to damage, degradation, or environmental hazards that occur during flight. Determining the causal factors and adverse events related to IVHM technologies will help in the formulation of research requirements and establish a list of example adverse conditions against which IVHM technologies can be evaluated. This paper documents the results of an examination of the most recent statistical/prognostic accident and incident data that is available from the Aviation Safety Information Analysis and Sharing (ASIAS) System to determine the causal factors of system/component failures and/or malfunctions in U.S. commercial aviation accidents and incidents

Assessment of the State of the Art of Integrated Vehicle Health Management Technologies as Applicable to Damage Conditions

A survey of literature from academia, industry, and other Government agencies assessed the state of the art in current integrated vehicle health management (IVHM) aircraft technologies. These are the technologies that are used for assessing vehicle health at the system and subsystem level. This study reports on how these technologies are employed by major military and commercial platforms for detection, diagnosis, prognosis, and mitigation. Over 200 papers from five conferences from the time period of 2004 to 2009 were reviewed. Over 30 of these IVHM technologies are then mapped into the 17 different adverse event damage conditions identified in a previous study. This study illustrates existing gaps and opportunities for additional research by the NASA IVHM Project

Identification of Crew-Systems Interactions and Decision Related Trends

NASA Vehicle System Safety Technology (VSST) project management uses systems analysis to identify key issues and maintain a portfolio of research leading to potential solutions to its three identified technical challenges. Statistical data and published safety priority lists from academic, industry and other government agencies were reviewed and analyzed by NASA Aviation Safety Program (AvSP) systems analysis personnel to identify issues and future research needs related to one of VSST's technical challenges, Crew Decision Making (CDM). The data examined in the study were obtained from the National Transportation Safety Board (NTSB) Aviation Accident and Incident Data System, Federal Aviation Administration (FAA) Accident/Incident Data System and the NASA Aviation Safety Reporting System (ASRS). In addition, this report contains the results of a review of safety priority lists, information databases and other documented references pertaining to aviation crew systems issues and future research needs. The specific sources examined were: Commercial Aviation Safety Team (CAST) Safety Enhancements Reserved for Future Implementation (SERFIs), Flight Deck Automation Issues (FDAI) and NTSB Most Wanted List and Open Recommendations. Various automation issues taxonomies and priority lists pertaining to human factors, automation and flight design were combined to create a list of automation issues related to CDM

Systems Analysis of NASA Aviation Safety Program: Final Report

A three-month study (February to April 2010) of the NASA Aviation Safety (AvSafe) program was conducted. This study comprised three components: (1) a statistical analysis of currently available civilian subsonic aircraft data from the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), and the Aviation Safety Information Analysis and Sharing (ASIAS) system to identify any significant or overlooked aviation safety issues; (2) a high-level qualitative identification of future safety risks, with an assessment of the potential impact of the NASA AvSafe research on the National Airspace System (NAS) based on these risks; and (3) a detailed, top-down analysis of the NASA AvSafe program using an established and peer-reviewed systems analysis methodology. The statistical analysis identified the top aviation "tall poles" based on NTSB accident and FAA incident data from 1997 to 2006. A separate examination of medical helicopter accidents in the United States was also conducted. Multiple external sources were used to develop a compilation of ten "tall poles" in future safety issues/risks. The top-down analysis of the AvSafe was conducted by using a modification of the Gibson methodology. Of the 17 challenging safety issues that were identified, 11 were directly addressed by the AvSafe program research portfolio

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper