The Boeing Company

Jay Kevin McCullough

Peter James Lake

Steven David Chapman

Shuguang Song

Stephen Robert Poteet

Anne Kao

Matthew Kyle Fay

David Charles Augustine

Ken D Bouvier

Steven C Runo

Yun-Ho Sikora

Lawrence C Wadle, Ii

Davis Scott Kinney

A method manages aircraft parts. A determination is made as to whether a no fault found parameter for a part type is greater than a no fault found threshold for an acceptable level for no fault found occurrences for the part type. The no fault found parameter is how often a no fault found for the part type occurs relative to how often that the part type has been removed and replaced. A determination is made as to whether an average fix time parameter is greater than a fix time threshold for a correct part replacement. The average fix time parameter identifies an average amount of time before a replaced part for the part type was replaced again. An alert is generated in response to the no fault found parameter being greater than the no fault found threshold and the average fix time parameter being greater than fix time threshold.

Aircraft maintenance system with no fault found part alerts

Aspects of the present disclosure provide a method and apparatus for maintenance recommendations. Embodiments include receiving data related to a plurality of fault codes. Embodiments include determining, for each respective fault code of the plurality of fault codes, a unique subset of parameters for the respective fault code based on frequencies of the parameters within the plurality of fault codes in the data. Embodiments include receiving a plurality of fault records and a plurality of maintenance records. Embodiments include, for each respective maintenance record of the plurality of maintenance record, identifying one or more candidate fault records of the plurality of fault records and correlating a subset of the one or more candidate fault records with the respective maintenance record based on the unique subset of the parameters for the respective fault code corresponding to each respective candidate fault record of the one or more candidate fault records.

Maintenance systems enhancement

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

Methods and systems are provided for managing a system that includes at least one component. The one component is removed from the system. If it is determined that the one component was removed from the system for a reason that is not failure of the one component, then it is indicated that the one component is potentially serviceable.

Fleet performance optimization tool enhancement

Methods and maintenance systems for use in analyzing data related to maintenance of at least one vehicle are disclosed. One example method includes retrieving, by a computing device, a plurality of diagnostic entries associated with at least one fault message from a database of diagnostic entries, each diagnostic entry including an identified corrective action and a date on which the identified corrective action was taken; identifying a plurality of groups of diagnostic entries, wherein the diagnostic entries in a group have a same corrective action, and each group has a confidence level associated with its corrective action; and weighting the confidence level for each group based on an age of the plurality of diagnostic entries in the group.

Maintenance systems and methods for use in analyzing maintenance data

Methods and systems are provided for enhancing performance of a system that includes a plurality of components. A server is coupled to a scanning device that is configured to scan a first component of the plurality of components for an identifier that uniquely identifies the first component. The server receives, from the scanning device, an identification of the first component of the plurality of components. The server also determines an operating parameter that is uniquely related to the first component, compares the operating parameter to a predefined baseline for the first component, and determines whether the first component is a rogue component.

Methods and maintenance systems for use in analyzing data related to maintenance of at least one vehicle are disclosed. One example method includes receiving at least one fault message, receiving a maintenance event log for a vehicle. The maintenance event log including at least one maintenance event associated with the at least one fault message. The example method further includes automatically identifying a corrective action within a most recent maintenance event of the at least one maintenance event and storing a diagnostic entry including the at least one fault message and the identified corrective action, such that the diagnostic entry is retrievable from the computing device to evaluate a subsequent like fault message.

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.

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Belleville, IL, United States of America

Jay Kevin McCullough