SYSTEMS AND METHODS FOR DETECTING AIRCRAFT MAINTENANCE EVENTS AND MAINTENANCE INTERVALS

• US 20150051786A1
• Filed: 08/15/2013
• Published: 02/19/2015
• Est. Priority Date: 08/15/2013
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Wang, Zhennong
• Granted Patent: US 10,723,487 B2
• Time in Patent Office: Days
• US Class Current: 701/29.4
• CPC Class Codes: B64F 5/60 Testing or inspecting aircraft components or systems

Abstract

A computing device for use in detecting maintenance events and maintenance intervals is provided. The computing device is configured to receive aircraft usage data for at least one carrier, identify at least one potential maintenance event in the usage data, identify at least one actual maintenance event in the usage data at least by comparing the usage data for a first aircraft of the at least one carrier to a second aircraft of the at least one carrier during each potential maintenance event, determine an indicator used by each carrier for scheduling maintenance events, determine a maintenance interval for each carrier for an aircraft model associated with at least the first aircraft.

Claims

1. A computing device for use in detecting maintenance events and maintenance intervals, said computing device comprising a processor coupled to a memory, said computing device is configured to:

receive aircraft usage data for at least one carrier;

identify at least one potential maintenance event in the usage data;

identify at least one actual maintenance event in the usage data at least by comparing the usage data for a first aircraft of the at least one carrier to the usage data for a second aircraft of the at least one carrier during each potential maintenance event;

determine, based at least in part on the usage data, that a decrease in usage of the first aircraft and the second aircraft is due to an exogenous event;

store an indication in said memory that the decrease in usage is due to the exogenous event;

determine an indicator used by each carrier for scheduling maintenance events; and

determine a maintenance interval for each carrier for an aircraft model associated with at least the first aircraft.

2. The computing device of claim 1, further configured to calculate at least one of cumulative flight hours, cumulative flight cycles, and cumulative aircraft ownership time, over a predetermined time period based on the usage data.

3. The computing device of claim 1, wherein the usage data includes flight hours, flight cycles, and aircraft ownership time and said computing device is further configured to:

determine that the indicator is one of the flight hours, the flight cycles, and the aircraft ownership time, based on calculating a distance between the flight hours, the flight cycles, and aircraft ownership time of the first aircraft and the second aircraft.

4. The computing device of claim 1, further configured to normalize variances in flight hours, flight cycles, and aircraft ownership time between at least one previous maintenance event and at least one newly mined event in the usage data.

5. The computing device of claim 1, further configured to identify a first potential maintenance event in the usage data based at least in part on a manufacturer-provided maintenance interval, using at least one of flight hours, flight cycles, and cumulative time for the at least one carrier.

6. The computing device of claim 1, further configured to calculate at least one of a duration between a first time period and a second time period based on the usage data, a difference between flight hours in the first time period and flight hours in the second time period based on the usage data, and a difference between flight cycles in the first time period and flight cycles in the second time period based on the usage data.

7. The computing device of claim 1, further configured to cluster multiple potential maintenance events from each aircraft of the at least one carrier based on at least one of a flight hours calculation, a flight cycles calculation, and a calculated duration between maintenance events.

8. The computing device of claim 1, further configured to compare at least two clusters and select one of the clusters with the least value of distance among flight hours, flight cycles and calculated duration within the cluster.

9. The computing device of claim 1, further configured to determine consequent maintenance events and intervals based on at least one previous interval that has been determined for the at least one carrier.

10. A method for use in detecting maintenance events and maintenance intervals, the method comprising:

receiving, at a computing device, aircraft usage data for at least one carrier;

identifying, by the computing device, at least one potential maintenance event in the usage data;

identifying, by the computing device, at least one actual maintenance event in the usage data at least by comparing the usage data for a first aircraft of the at least one carrier to the usage data for a second aircraft of the at least one carrier during each potential maintenance event;

determining, by the computing device, based at least in part on the usage data, that a decrease in usage of the first aircraft and the second aircraft is due to an exogenous event,

storing an indication in a memory coupled to the computing device that the decrease in usage is due to the exogenous event,

determining, by the computing device, an indicator used by each carrier for scheduling maintenance events; and

determining, by the computing device, a maintenance interval for each carrier for an aircraft model associated with at least the first aircraft.

11. The method of claim 10, further comprising calculating at least one of cumulative flight hours, cumulative flight cycles, and cumulative aircraft ownership time, over a predetermined time period based on the usage data.

12. The method of claim 10, further comprising:

determining that a first carrier of the at least one carrier is identified by a first name and a second name in the usage data; and

replacing the second name with the first name in the usage data.

13. The method of claim 10, wherein the usage data includes flight hours, flight cycles, and aircraft ownership time, the method further comprising:

determining that the indicator is one of the flight hours, the flight cycles, and the aircraft ownership time, based on calculating a distance between the flight hours, the flight cycles, and the aircraft ownership time of the first aircraft and the second aircraft.

14. The method of claim 10, further comprising normalizing variances in flight hours, flight cycles, and aircraft ownership time between at least one previous maintenance event and at least one newly mined event in the usage data.

15. The method of claim 10, further comprising identifying a first potential maintenance event in the usage data based at least in part on a manufacturer-provided maintenance interval, using at least one of flight hours, flight cycles, and cumulative time for the at least one carrier.

16. The method of claim 10, further comprising calculating a difference between flight hours in a first time period and flight hours in a second time period based on the usage data, a duration between the first time period and the second time period based on the usage data, and a difference between flight cycles in the first time period and flight cycles in the second time period based on the usage data.

17. The method of claim 10, further comprising clustering multiple potential maintenance events from each aircraft of the at least one carrier based on at least one of a flight hours calculation, a flight cycles calculation, and a calculated duration between maintenance events.

18. The method of claim 10, further comprising comparing at least two clusters and selecting one of the clusters with the least value of distance among flight hours, flight cycles and calculated duration within the cluster.

19. The method of claim 10, further comprising determining consequent maintenance events and intervals based on at least one previous interval that has been determined for the at least one carrier.

20. A non-transitory computer-readable storage device having computer-executable instructions embodied thereon for use in detecting maintenance events and maintenance intervals, wherein, when executed by a computing device including a processor coupled to a memory, the computer-executable instructions cause the computing device to:

receive aircraft usage data for at least one carrier;

identify at least one potential maintenance event in the usage data;

identify at least one actual maintenance event in the usage data at least by comparing the usage data for a first aircraft of the at least one carrier to the usage data for a second aircraft of the at least one carrier during each potential maintenance event;

determine, based at least in part on the usage data, that a decrease in usage of the first aircraft and the second aircraft is due to an exogenous event;

store an indication in the memory that the decrease in usage is due to the exogenous event;

determine an indicator used by each carrier for scheduling maintenance events; and

determine a maintenance interval for each carrier for an aircraft model associated with at least the first aircraft.