公开(公告)号：US20230186238A1

公开(公告)日：2023-06-15

申请号：US18165184

申请日：2023-02-06

Applicant: THE BOEING COMPANY

Inventor： Zhennong WANG ,  Yun SHI

IPC: G06Q10/0875 ,  G06Q30/0601 ,  G06Q10/063 ,  G06Q30/0201 ,  G06Q30/0202

CPC classification number: G06Q10/0875 ,  G06Q30/0633 ,  G06Q10/063 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q10/0838

Abstract: Techniques for intelligently predicting bundles of replacement parts. These techniques include determining a plurality of maintenance events for a plurality of replacement parts. The determining includes identifying one or more replacement parts for a maintenance event, based on one or more replacement part events occurring within a time period related to the maintenance event. The techniques further include generating one or more clusters of replacement parts based on the plurality of maintenance events, and predicting one or more bundles of replacement parts, based on the clusters, wherein each bundle comprises a plurality of replacement parts.

公开(公告)号：US20220281618A1

公开(公告)日：2022-09-08

申请号：US17751647

申请日：2022-05-23

Applicant: THE BOEING COMPANY

Inventor： Zhennong WANG

IPC: B64F5/60 ,  G06F30/20 ,  G07C5/00 ,  G07C5/08

Abstract: The present disclosure provides for predictive part maintenance by generating a reliability curve for an aircraft based on historic removals; setting a removal threshold on the reliability curve; tracking an installation of a given instance of the aircraft part into a given aircraft; tracking a number of cycles of the given instance of the aircraft part based on operations of the given aircraft in which the given instance of the aircraft part is installed; and in response to the number of cycles of the given instance of the aircraft part satisfying the removal threshold, transmitting a service alert to an operator of the given aircraft.

公开(公告)号：US20210182788A1

公开(公告)日：2021-06-17

申请号：US17175991

申请日：2021-02-15

Applicant: THE BOEING COMPANY

Inventor： Zhennong WANG ,  Yun Shi

IPC: G06Q10/08 ,  G06Q30/06 ,  G06Q10/06 ,  G06Q30/02

Abstract: Techniques for intelligently predicting bundles of replacement parts. A plurality of maintenance events for a plurality of replacement parts are determined based on historical data related to the plurality of replacement parts. Each maintenance event of the plurality of maintenance events corresponds with one or more of the replacement parts. A plurality of clusters of replacement parts are generated based on the plurality of maintenance events. A plurality of bundles of replacement parts are predicted based on the clusters. Each bundle includes a plurality of replacement parts.