The Boeing Company

Ranjan Kumar Paul

Liessman E Sturlaugson

Shuguang Song

Sabyasachi Basu

Rodney Allen Tjoelker

Anbessie A Yitbarek

Shuying Zhu

John B Maggiore

William R Frans

I-Li Lu

Farshad Dopulatshahi

Christopher David Deits

Elizabeth A Whalen

Peter A Fiddler

Roman D Fresnedo

Valeria V Thompson

Virginia L Wheway

A maintenance interval adjuster and methods for improving accuracy of maintenance scheduling and changing a maintenance interval are presented. Scheduled maintenance data and unscheduled in-service maintenance data for a maintenance task are retrieved for a plurality of platforms. A distribution of lifetimes for the maintenance task in the scheduled maintenance data and unscheduled in-service maintenance data are analyzed for high variance or multiple modes. A number of conditions in sensor data of the plurality of platforms correlated to a length of the lifetimes for the maintenance task is identified, in response to identifying at least one of high variance or multiple modes in the distribution of lifetimes. The lifetimes are divided into a plurality of groups based on the number of conditions. A respective recommended maintenance interval is determined for each group of the plurality of groups based on respective lifetimes for the maintenance task of a respective group.

Adjusting maintenance intervals for individual platforms based on observable conditions

A computer implemented method, apparatus, and computer program product for identifying an interval for performing a maintenance task. The process retrieves scheduled maintenance data and un-scheduled in-service maintenance data for a given apparatus type. The process maps the un-scheduled in-service maintenance data to the scheduled maintenance data for the given apparatus type to form mapped maintenance data. The process performs a statistical analysis on the mapped maintenance data. The process identifies an optimal interval for performing the maintenance task based on a result of the statistical analysis to form a recommended maintenance interval.

Statistical analysis for maintenance optimization

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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Sammamish, WA, United States of America

Ranjan Kumar Paul