The Boeing Company

Shuguang Song

Peter James Lake

Jay Kevin McCullough

Ken D Bouvier

Matthew Kyle Fay

Sabyasachi Basu

Ranjan Kumar Paul

Rodney Allen Tjoelker

Roberto E Altschul

William R Frans

Brian C Fredgren

John B Maggiore

Ranjan K Paul

Roman D Fresnedo

Valeria V Thompson

Virginia L Wheway

Fritz Scholz

Rodney A Tjoelker

A computer-based method for determining an effect of operational readiness for a vehicle in a fleet of vehicles based on a component replacement simulation is described. The method includes querying, using a fleet performance optimization tool, a maintenance data database. The method also includes analyzing the data set using a power law process to predict a next component removal for each vehicle based on hours of operation for each vehicle. The method also includes determining an effect of operational readiness for the selected vehicle based on the simulation. The method further includes ranking each vehicle in the fleet of vehicles based on the operational readiness of each vehicle. The method also includes displaying, based on the ranking, the operational readiness of each vehicle on the user interface to facilitate actual replacement of at least one component on at least one of the vehicles.

Step analysis process steps within a fleet performance optimization tool

A system is provided for maintenance of a manufactured product composed of a plurality of parts. A modeling engine may receive failure data for the plurality of parts in which the failure data indicates individual instances of failure of at least two of a multiple quantity of a part of the plurality of parts. Each of the at least two of the multiple quantity may be located at a respective distinct location in the manufactured product. The modeling engine may generate a superimposed failure model (SFM) for the part, including determining a lifetime distribution of the part based at least partially on application of a lifetime distribution model to the SFM. A maintenance engine coupled to the modeling engine may perform a maintenance activity including determining a maintenance interval determined for the part according to the lifetime distribution of the part.

System for maintenance of a manufactured product

A Maintenance Interval Determination and Optimization Tool (MIDOT) provides optimized maintenance schedules for performing maintenance tasks on one or more components or systems based on component survival functions and economic analysis of non-safety tasks associated with maintenance schedules. MIDOT is used for specified platforms such as aircrafts. The MIDOT filters maintenance history data, uses a statistical analysis to predict likely maintenance needs, and performs an economic analysis to optimize aircraft maintenance schedules. Specifically, the MIDOT calculates component survival probability, based on the specific usage of one or more related components within the platform and determines an optimal maintenance task interval to perform a maintenance task associated with the one or more related components.

Maintenance interval determination and optimization tool and method

A computer-based method for simulating an overall effect of a component replacement on the reliability of a platform is described. The method includes determining a scheduled reliability for a platform based on a reliability associated with each of the removable components of the platform, selecting, via a user interface, at least one removable component of the platform for which replacement is to be simulated, determining, using a computer-based model, an effect the one or more replacements would have on the forecasted reliability for the platform, and providing a comparison of the forecasted reliability and the scheduled reliability to a user.

Fleet performance optimization tool for aircraft health management

A system, method, and computer program product for predicting failure of a vehicle system or subsystem by using statistical analysis of prior maintenance messages and vehicle failures, such that the predictions of failures may be incorporated into a vehicle monitoring and reporting system. Maintenance message data and vehicle system or subsystem failure data are collected from a central maintenance computer of a vehicle, such as an aircraft. This maintenance message and vehicle system or subsystem failure data are analyzed to discern relationships between maintenance messages and vehicle system or subsystem failures which will enable future failures to be predicted. By predicting future failures, maintenance can be performed in time to prevent the vehicle failure and thereby avoid unnecessary costs and unscheduled interruptions of vehicle operations.

System, method, and computer program product for fault prediction in vehicle monitoring and reporting system

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Seattle, WA, United States of America

Shuguang Song