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Mock-Ups, Models, Simulations, and Embedded Testing
Published in Samuel G. Charlton, Thomas G. O’Brien, Handbook of Human Factors Testing and Evaluation, 2019
Valerie J. Gawron, Thomas W. Dennison, Michael A. Biferno
Embedded testing during normal product operation is conducted in some industries to improve performance-prediction accuracy. One of the most comprehensive applications of this approach is found in an FAA sponsored program, where commercial airline pilot performance is measured and documented on an advanced flight recorder as part of standard airline operations. The Flight Operations Quality Assurance (FOQA) program provides a means to manage risk and detect trends in flight crew performance before they turn into costly incidents (Penny & Giles Aerospace, 1996). In this situation we have the real operators in the real operational environment being measured on parameters that are directly related to safety (e.g., takeoff and landing performance). When an airline’s pilots show unacceptable performance in a class of tasks, the airline and manufacturer can look into the need for improved systems, training, work/rest schedules, or other remedies. Embedded testing offers the operator and the manufacturer an opportunity to identify and understand performance problems before they cause injury or economic loss.
Applying Crew Resource Management Theory and Methods to the Operational Environment
Published in Pamela S. Tsang, Michael A. Vidulich, Principles and Practice of Aviation Psychology, 2002
In recognition of this, Helmreich et al. (1999b) have called for a more comprehensive approach to the construction and evaluation of CRM training. They advocate using five main sources of data on flight operations to continually revise and improve CRM training: (a) training and checking evaluations of pilots (by those who have themselves undergone CRM training), (b) incident reports, (c) flight data from Flight Operations Quality Assurance (FOQA) programs, (d) attitude surveys of aircrews, and (e) observations of line operations by trained observers. The data sources are seen as reflective of the “big picture,” as they encompass the flight deck environment and the organizational milieu within which flight deck operations take place.
History and Evolution of Safety
Published in Alan J. Stolzer, Carl D. Halford, John J. Goglia, Safety Management Systems in Aviation, 2018
Alan J. Stolzer, Carl D. Halford, John J. Goglia
Flight Operations Quality Assurance Flight Operations Quality Assurance (FOQA) is regarded as the most objective of the proactive safety programs, in that it collects data recorded by an aircraft’s flight data acquisition and recording systems and aggregates it into a database that incorporates a part or all of an airline’s fleet (FAA, 2004). Routine flight operations are then analyzed by sophisticated software that identifies exceedances and trends. Every approved program must demonstrate some means of using the intelligence gathered from this analysis in the mitigation of risk.
The Link between Individual Predictors of Risk and Risky Flight Behavior: A Systematic Review
Published in The International Journal of Aerospace Psychology, 2023
Yassmin Ebrahim, Brett R. C. Molesworth, Oleksandra Molloy
Certain objective risk measures are less susceptible to individual influences (Young et al., 2007). In aviation, simulated flight, operational flight data (i.e., Flight Operational Quality Assessment (FOQA) data) often provide a more accurate insight into how pilots assess risk on the flight deck, than self-reported measures. These methods are often used for training and competency. Simulated flight or FOQA data allow for, as much as possible true (flight) behavior to be assessed, with pilots utilizing their experience, training, and their innate personality tendencies to determine the most appropriate action in a certain situation. Simulated flight allows for a variety of scenarios to assess propensity to engage in risk, such as critical system failures which are unethical or highly dangerous if performed in an operational setting.