Process and system for multi-objective global optimization of maintenance schedules

• US 20080234979A1
• Filed: 03/19/2007
• Published: 09/25/2008
• Est. Priority Date: 03/19/2007
• Status: Active Grant

• Current Assignee: Raytheon Technologies Corporation d/b/a RTX
• Original Assignee: United Technologies Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Khibnik, Alexander I., Wang, Jihua, Winston, Howard A., Ireland, Julie A., Rajamani, Ravi, Cohen, Robert M., Costiner, Sorin, Benitez, Ricardo A., Cohen, Ellen, Matthis, Thomas R.
• Granted Patent: US 8,396,571 B2
• Time in Patent Office: Days
• US Class Current: 702/184
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A process for optimizing maintenance work schedules for at least one engine includes the steps of retrieving at least one set of data for an engine from a computer readable storage medium; selecting at least one scheduling parameter for the engine; selecting a set of maintenance rules for the engine; selecting at least one maintenance work decision; selecting at least one objective for the engine; optimizing the at least one objective to generate at least one optimal maintenance work decision; and generating at least one optimal maintenance work schedule for the engine.

Claims

1. A process for optimizing maintenance work schedules for at least one engine, comprising:

retrieving at least one set of data for an engine from a computer readable storage medium;

selecting at least one scheduling parameter for said engine;

selecting a set of maintenance rules for said engine;

selecting at least one maintenance work decision;

selecting at least one objective for said engine;

optimizing said at least one objective to generate at least one optimal maintenance work decision; and

generating at least one optimal maintenance work schedule for said engine.

2. The process of claim 1, wherein the optimization step comprises the steps of:

evaluating said at least one objective, said at least one data and said at least one simulated maintenance work decision based upon a set of engine life realizations;

constructing a scheduled maintenance plan based upon the evaluation step;

generating a projected cost of at least one maintenance work decision based upon the construction step; and

selecting at least one cost effective maintenance work decision; and

optimizing said at least one objective based upon said at least one cost effective maintenance work decision.

3. The process of claim 2, wherein the evaluation step comprises using any one of the following approaches:

deterministic approach and stochastic approach.

4. The process of claim 1, wherein the selection step of said at least one scheduling parameter comprises selecting said at least one scheduling parameter based upon said at least one set of data.

5. The process of claim 1, wherein the selection step of said set of maintenance rules comprises selecting said set of maintenance rules based upon the selection of said at least one scheduling parameter.

6. The process of claim 1, wherein the selection step of said at least one maintenance work decision comprises the following steps:

accepting said at least one scheduling parameter;

incorporating said set of maintenance rules; and

determining said at least one maintenance work decision based upon said at least one scheduling parameter and said set of maintenance rules.

7. The process of claim 6, wherein the determination step comprises processing said at least one scheduling parameter and said set of maintenance rules using any one of the following approaches:

deterministic approach and stochastic approach.

8. The process of claim 1, wherein the selection step of said at least one objective comprises generating said at least one objective based upon said at least one data and said at least one simulated maintenance work decision.

9. The process of claim 1, wherein the generation step comprises generating at least one optimal maintenance work schedule based upon said at least one optimal maintenance work decision.

10. A system comprising a computer readable storage device readable by the system, tangibly embodying a program having a set of instructions executable by the system to perform the following steps for optimizing maintenance work schedules for at least one engine, the system comprising:

means for retrieving at least one set of data for an engine from a computer readable storage device;

means for selecting at least one scheduling parameter for said engine;

means for selecting a set of maintenance rules for said engine;

means for selecting at least one maintenance work decision;

means for selecting at least one objective for said engine;

means for optimizing said at least one objective to generate at least one optimal maintenance work decision; and

means for generating at least one optimal maintenance work schedule for said at least one engine.

11. The system of claim 10, wherein the instruction to optimize comprises:

means for evaluating said at least one objective, said at least one data and said at least one simulated maintenance work decision based upon a set of engine life realizations;

means for constructing a scheduled maintenance plan based upon the evaluation step;

means for generating a projected cost of at least one maintenance work decision based upon the construction step; and

means for selecting at least one cost effective maintenance work decision; and

means for optimizing said at least one objective based upon said at least one cost effective maintenance work decision.

12. The system of claim 11, wherein means for evaluating comprises means for using any one of the following approaches:

deterministic approach and stochastic approach.

13. The system of claim 11, wherein means for selecting said at least one scheduling parameter comprises means for selecting said at least one scheduling parameter based upon said at least one set of data.

14. The system of claim 11, wherein means for selecting said set of maintenance rules comprises means for selecting said set of maintenance rules based upon the selection of said at least one scheduling parameter.

15. The system of claim 11, wherein means for selecting said at least one maintenance work decision comprises:

means for accepting said at least one scheduling parameter;

means for incorporating said set of maintenance rules; and

means for determining said at least one maintenance work decision based upon said at least one scheduling parameter and said set of maintenance rules.

16. The system of claim 15, wherein means for determining comprises means for processing said at least one scheduling parameter and said set of maintenance rules and to use any one of the following approaches:

deterministic approach and stochastic approach.

17. The system of claim 11, wherein means for selecting said at least one objective comprises means for generating said at least one objective based upon said at least one data and said at least one simulated maintenance work decision.

18. The system of claim 11, wherein means for generating comprises means for generating at least one optimal maintenance work schedule based upon said at least one optimal maintenance work decision.

19. A process for optimizing maintenance work schedules for at least one industrial system, comprising:

retrieving at least one set of data for at least one industrial system from a computer readable storage medium;

selecting at least one scheduling parameter for said at least one industrial system;

selecting a set of maintenance rules for said at least one industrial system;

selecting at least one maintenance work decision for said at least one industrial system;

selecting at least one objective for said at least one industrial system;

optimizing said at least one objective to generate at least one optimal maintenance work decision for said at least one industrial system; and

generating at least one optimal maintenance work schedule for said at least one industrial system.

20. The process of claim 19, wherein the optimization step comprises the steps of:

evaluating said at least one objective, said at least one data and said at least one simulated maintenance work decision based upon a set of engine life realizations;

constructing a scheduled maintenance plan based upon the evaluation step;

generating a projected cost of at least one maintenance work decision based upon the construction step; and

selecting at least one cost effective maintenance work decision; and

optimizing said at least one objective based upon said at least one cost effective maintenance work decision.

21. The process of claim 20, wherein the evaluation step comprises using any one of the following approaches:

deterministic approach and stochastic approach.

22. The process of claim 19, wherein the selection step of said at least one scheduling parameter comprises selecting said at least one scheduling parameter based upon said at least one set of data.

23. The process of claim 19, wherein the selection step of said set of maintenance rules comprises selecting said set of maintenance rules based upon the selection of said at least one scheduling parameter.

24. The process of claim 19, wherein the selection step of said at least one maintenance work decision comprises the following steps:

accepting said at least one scheduling parameter;

incorporating said set of maintenance rules; and

determining said at least one maintenance work decision based upon said at least one scheduling parameter and said set of maintenance rules.

25. The process of claim 24, wherein the determination step comprises processing said at least one scheduling parameter and said set of maintenance rules using any one of the following approaches:

deterministic approach and stochastic approach.

26. The process of claim 19, wherein the selection step of said at least one objective comprises generating said at least one objective based upon said at least one data and said at least one simulated maintenance work decision.

27. The process of claim 19, wherein the generation step comprises generating at least one optimal maintenance work schedule based upon said at least one optimal maintenance work decision.