Federal Express Corporation

Suresh Rangan

Robert E Fisher

James L Bowman

An in-flight risk management system includes an eye sensor, a seat sensor, and one or more in-flight risk management computers that perform operations including: obtaining history information for a flight crew member, obtaining flight information associated with a flight on which the flight crew member will be present, determining, based on the history information and the flight information, a predicted fatigue profile for the flight crew member, determining, based on the predicted fatigue profile for the crew member, one or more fatigue indicator profiles for the flight crew member, obtaining, from at least one of the eye sensor or seat sensor, one or more measured fatigue indicator values associated with the flight crew member, generating, based on the one or more measured fatigue indicator values, one or more updated fatigue indicator profiles, and generating, based on the one or more updated fatigue indicator profiles, an updated predicted fatigue profile.

Mitigating operational risk in aircraft

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving data related to a first flight risk factor and a second flight risk factor where the first and second risk factors include one of: a proficiency risk factor, an equipment risk factor, an environmental risk factor, or a performance risk factor. Applying a first weighting to the first flight risk factor to generate a first weighted flight risk factor, and applying a second weighting to the second flight risk factor to generate a second weighted flight risk factor. Assessing a flight risk level for a flight based on the first weighted flight risk factor and the second weighted flight risk factor. Providing data indicating the assessed flight risk level for the flight for display to a user.

Risk assessment framework

There is provided a research framework system. For example, in some implementations there is provided a sleep prediction system for pilots including a first data structure storing collected research data related to pilot sleep patterns, a second data structure storing data related to a flight schedule associated with a pilot, and a sleep prediction module configured to access the data stored in the first and second data structures and calculate, by one or more processors using the data stored in the first data structure, a likelihood that the pilot associated with the flight schedule stored in the second data structure is sleeping at a given time.

Research performance framework

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving data related to a first flight risk factor and a second flight risk factor where the first and second risk factors include one of: a proficiency risk factor, an equipment risk factor, an environmental risk factor, or a performance risk factor. Applying a first weighting to the first flight risk factor to generate a first weighted flight risk factor, and applying a second weighting to the second flight risk factor to generate a second weighted flight risk factor. Assessing a flight risk level for a flight based on the first weighted flight risk factor and the second weighted flight risk factor, Providing data indicating the assessed flight risk level for the flight for display to a user.

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Germantown, TN, United States of America

Suresh Rangan