American Airlines, Inc.

Steven James Oakley

Mei Zhang

Jose Antonio Ramirez-Hernandez

Ou Bai

Ning Xu

Supreet Reddy Mandala

Tuell Coleman Green

Shau-Shiang Sunny Ja

Nancy Lee Lillo

Sameer Anand

Louis Matthew Pfeifer

Alejandro Edgardo Scalise

A system according to which a network of physical sensors are configured to detect and track the performance of aircraft engines. The physical sensors are placed in specific locations to detect an exhaust gas temperature, vibration, speed, oil pressure, and fuel flow for each aircraft engine. The performance of each aircraft engine is then viewed in combination with oil consumption associated with that aircraft engine and the routine maintenance program associated with that aircraft engine to route the aircraft and move the aircraft, in accordance with the routing, to a specific location. The sensors efficiently track the performance and physical condition of the engines. Moreover, a listing of identified 'at-risk' engines is displayed on a screen of a GUI in a manner that allows for easy navigation and display. Data point(s) that triggered the identification of each “at-risk” engine are easily accessible and viewable.

Method and system of predicting maintenance events using machine learning model(s) and a training data set

A system according to which a network of physical sensors are configured to detect and track the performance of aircraft engines. The physical sensors are placed in specific locations to detect an exhaust gas temperature, vibration, speed, oil pressure, and fuel flow for each aircraft engine. The performance of each aircraft engine is then viewed in combination with oil consumption associated with that aircraft engine and the routine maintenance program associated with that aircraft engine to route the aircraft and move the aircraft, in accordance with the routing, to a specific location. The sensors efficiently track the performance and physical condition of the engines. Moreover, a listing of identified 'at-risk' engines is displayed on a screen of a GUI in a manner that allows for easy navigation and display. Data point(s) that triggered the identification of each 'at-risk' engine are easily accessible and viewable.

Predictive sensor system for aircraft engines with graphical user interface

A system and method according to which a recommended quantity of spare engine components is generated. In several exemplary embodiments, the components support aircraft maintenance and flight operations and are designed to be repaired periodically. In an exemplary embodiment, the recommended quantity is a number of available spare engine components that supports the aircraft maintenance operations but avoids excess spare engine components in inventory.

Spare component ownership planning system and method

A system and method for inventory management is provided. An indication of a removal of a first resource at a first location is received, and a risk value associated with the first resource at the location is calculated. A determination is made if the risk value is less than a predetermined threshold, and a request to transfer a second resource from a second location to the first location is generated.

System and method for inventory management and distribution

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North Richland Hills, TX, United States of America

Steven James Oakley