Prediction of maintenance operations on an aircraft engine

• US 8,868,287 B2
• Filed: 02/23/2012
• Issued: 10/21/2014
• Est. Priority Date: 02/25/2011
• Status: Active Grant

• Current Assignee: Safran Aircraft Engine Company
• Original Assignee: Snecma (Safran SA)
• Inventors: Autier, Jean-Philippe, Gendronneau, Eric, Delaye, Guillaume
• Primary Examiner(s): Holloway, Jason
• Assistant Examiner(s): Bendidi, Rachid
• Application Number:
  US13/403,272
• Publication Number:
  US 20120221193A1
• Time in Patent Office: 971 Days
• Field of Search: 701/29, 701/29.1, 701/29.4, 701/30, 701/31.4, 701/31.9, 701/34.4, 705/7
• US Class Current: 701/31.9
• CPC Class Codes: F05D 2230/72 Maintenance
• CPC Class Codes: F05D 2260/80 Diagnostics
• CPC Class Codes: F05D 2260/82 Forecasts
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06

Abstract

The invention relates to a method and a system for predicting maintenance operations on a current aircraft engine, comprising:

• • processing means to compare a set of failure models (M1, . . . , Mn) adapted to said current engine to select a relevant failure model (Mi) with a failure age (T₀) defining the age of said engine at the time of the failure;
  • processing means to associate decision rules (R) about the workscope on said current engine with said relevant failure model (Mi), as a function of a set of parameters (P1, P2, Pi) related to said current engine; and
  • processing means to determine the required maintenance workscope (Wf) to be applied to said current engine, as a function of said decision rules.

Claims

1. A method for predicting maintenance operations on a current aircraft engine, comprising:

determining, using a processor and a simulation on a set of failure models associated with the current aircraft engine, a failure age corresponding to an age of the current engine at a time of failure, for each failure model of the set of failure models, each said failure model corresponding to a given failure and being represented by a law for the cumulated probability of failure as a function of time expressed in terms of flight cycles;

selecting, using the processor, a relevant failure model by selecting one of said failure models of said set of failure models, the relevant failure model having a minimum failure age;

determining, using the processor, a relevant first rules module corresponding to the relevant failure model, the relevant first rules module defining a plurality of workscopes as a function of the age of the current aircraft engine expressed in terms of flight cycles;

from the plurality of workscopes of the relevant first rules module, selecting, using the processor, a relevant minimum workscope associated with the minimum failure age; and

determining, using the processor, a required final maintenance workscope to be done on the current aircraft engine from the relevant minimum workscope and from a required number of flight cycles before a next maintenance operation.

2. The method according to claim 1, wherein said determining the failure age is based on input of a set of parameters, the set of parameters including the following parameters:

failure age, operating duration of the current engine since a last shop visit, rank of a shop visit, potential remaining life for each of a plurality of life limited parts (LLP) of the current engine, and reconstruction constraints of the current engine.

3. The method according to claim 2, wherein said set of parameters is modified after a maintenance operation on the current aircraft engine has been done.

4. The method according to claim 1, wherein said first rules module is selected from among a set of first rules modules defined previously during an initialization phase, each of said first rules modules being associated with a determined failure model and a determined rank of a shop visit.

5. The method according to claim 1, wherein said failure models are derived from analysis of operating experience on a fleet of engines including data regarding a number of engines, an operating environment of each engine, a model of each engine, an operational condition of each engine, a maintenance location of each engine, and a duration between entry of each engine in a workshop and its exit from the workshop.

6. The method according to claim 1, wherein the minimum failure age defines a predicted age of the current aircraft engine at the time of failure.

7. The method according to claim 1, wherein the minimum failure age indicates a date of a shop visit, and said determining the required final maintenance workscope indicates a workscope to be performed at the date of the shop visit.

8. The method according to claim 1, wherein said selecting the relevant failure model includes selecting the relevant failure model having the minimum failure age from among a set of failure ages corresponding to said set of failure models.

9. The method according to claim 1, wherein each said failure model of the set of failure models corresponds to a different cause of failure for the current aircraft engine.

10. A system for predicting maintenance operations on a current aircraft engine, comprising:

processing circuitry configured to

determine, using a simulation on a set of failure models associated with the current aircraft engine, a failure age corresponding to an age of the current engine at a time of failure, for each failure model of the set of failure models, each said failure module corresponding to a given failure and being represented by a law for the cumulated probability of failure as a function of time expressed in terms of flight cycles;

select a relevant failure model by selecting one of said failure models of said set of failure models, the relevant failure model having a minimum failure age;

determine a relevant first rules module corresponding to the relevant failure model, the relevant first rules module defining a plurality of workscopes as a function of the age of the current aircraft engine expressed in terms of flight cycles;

from the plurality of workscopes of the relevant first rules module, select a relevant minimum workscope associated with the minimum failure age; and

determine a required final maintenance workscope to be done on the current aircraft engine from the relevant minimum workscope and from a required number of flight cycles before a next maintenance operation.

11. A non-transitory computer-readable storage medium storing computer-readable instructions that, when executed by a computer, cause the computer to perform a method comprising:

determining, using a simulation on a set of failure models associated with the current aircraft engine, a failure age corresponding to an age of the current engine at a time of failure, for each failure model of the set of failure models, each said failure module corresponding to a given failure and being represented by a law for the cumulated probability of failure as a function of time expressed in terms of flight cycles;

selecting a relevant failure model by selecting one of said failure models of said set of failure models, the relevant failure model having a minimum failure age;

determining a relevant first rules module corresponding to the relevant failure model, the relevant first rules module defining a plurality of workscopes as a function of the age of the current aircraft engine expressed in terms of flight cycles;

from the plurality of workscopes of the relevant first rules module, selecting a relevant minimum workscope associated with the minimum failure age; and

determining a required final maintenance workscope to be done on the current aircraft engine from the relevant minimum workscope and from a required number of flight cycles before a next maintenance operation.