Rotable inventory calculation method

• US 7,647,255 B2
• Filed: 01/23/2004
• Issued: 01/12/2010
• Est. Priority Date: 01/23/2004
• Status: Expired due to Fees

• Current Assignee: United Technologies Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Original Assignee: United Technologies Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Gannon, Thomas, Tomastik, Robert, Wang, Jihua, Rajamani, Ravi
• Primary Examiner(s): Gart; Matthew S.
• Assistant Examiner(s): Zare; Scott A
• Application Number:
  US10/763,803
• Publication Number:
  US 20050177467A1
• Time in Patent Office: 2,181 Days
• Field of Search: 705/28
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

A method for conducting a repairable inventory analysis calculates the minimum number of repairable parts to be held in inventory while still being able to satisfy the demand for spare parts even in view of uncertain repair lead times. The method uses a set of equations that relates a customer service level to arbitrary probability distribution functions of a repair lead-time and a part arrival process. The distributions are then searched to locate the optimal inventory level in the distribution.

Claims

1. A method of optimizing rotable inventory, comprising:

interfacing a processor with a user interface, the user interface and the processor communicating with a computer having a computer readable storage medium including instructions for executing an algorithm to determine an optimized inventory level, the algorithm comprising the steps of;

selecting a desired customer service level;

obtaining at least one characteristic of a part repair lead-time distribution, wherein the at least one characteristic is a mean μ and

a variance σ

of the part repair lead-time distribution;

computing on the computer a proposed inventory level based on said at least one characteristic, wherein computing a proposed inventory level includes recomputing a probability term β

having a distribution reflected by a difference term Δ

_β

and calculating the proposed inventory level as I=A·

(R−

W)−

μ

+Δ

_β

·

σ

, wherein I is the proposed inventory level, A is a part arrival value, R is a maximum repair time and W is a desired turnaround time window;

determining a calculated customer service level corresponding to the proposed inventory level;

comparing the calculated customer service level with the desired customer service level; and

selecting the proposed inventory level as the optimized inventory level when the calculated customer service level is within a selected convergence threshold with respect to the desired customer service level.

2. The method of claim 1, wherein the probability term β

is bound by a left bound value BL and a right bound value BR, and wherein the method further comprises;

shifting the probability term β

to the left bound value BL and defining a new probability term β

between the left bound value BL and the right bound value BR if the calculated customer service level is less than the desired customer service level; and

shifting the probability term β

to the right bound value BR and defining a new probability term β

between the left bound value BL and the right bound value BR if the calculated customer service level is greater than the desired customer service level and if the difference between the calculated customer service level and the desired customer service level is greater than the selected convergence threshold.

3. The method of claim 2, further comprising repeating the computing, determining, comparing and shifting steps until the selecting step is executed.

4. The method of claim 1, further comprising repeating the computing, determining, and comparing steps until the selecting step is executed.

5. The method of claim 1, wherein the desired customer service level is a desired on-time delivery, and the calculated customer service level is a mean on-time delivery, wherein the desired on-time delivery and the mean on-time delivery are represented by a mean of a number of on-time delivered parts per time unit divided by a mean of arrivals per time unit.

6. The method of claim 5, wherein a number of arrivals per time unit is a constant number, and wherein the mean of arrivals per time unit is set equal to the constant number.

7. The method of claim 1, wherein the part arrival value is randomly variable.

8. The method of claim 7, wherein the method further comprises:

obtaining an arrival value having a distribution G and an inventory value having a distribution Φ

;

obtaining a distribution of the calculated customer service level based from the distributions G and Φ

; and

conducting the step of determining the calculated customer service level based on the distribution of the calculated customer service level.

9. The method of claim 7, wherein the method further comprises approximating the randomly variable number of arrivals per time unit with a constant number of arrivals per time unit.

10. The method of claim 1, wherein the method optimizes rotable inventory for an asset having a plurality of individual parts, wherein the step of selecting the desired customer service level comprises selecting the desired customer service level for the plurality of individual parts, and wherein the method further comprises:

conducting the obtaining, computing, determining, comparing, and selecting steps to obtain the optimized inventory level for each of said plurality of parts;

summing the optimized inventory level for each of the plurality of individual parts to obtain a total optimized inventory level;

calculating a total rotable inventory cost from the total optimized inventory level; and

minimizing the total rotable inventory cost.

11. The method of claim 10, wherein the minimizing step is conducted via a constrained optimization process.

12. A method of maintaining an optimized rotable inventory level, comprising:

determining an optimized inventory level, the determining step occurring on a computer having a computer readable storage medium storing instructions for;

selecting a desired customer service level;

obtaining at least one characteristic of a part repair lead-time distribution, wherein the at least one characteristic is a mean μ and

a variance σ

of the part repair lead-time distribution;

computing on the computer a proposed inventory level based on said at least one characteristic, wherein computing a proposed inventory level includes recomputing a probability term β

having a distribution reflected by a difference term Δ

_β

and calculating the proposed inventory level as I=A·

(R−

W)−

μ

+Δ

_β

·

σ

, wherein I is the proposed inventory level, A is a part arrival value, R is a maximum repair time and W is a desired turnaround time window;

determining a calculated customer service level corresponding to the proposed inventory level;

comparing the calculated customer service level with the desired customer service level; and

selecting the proposed inventory level as the optimized inventory level when the calculated customer service level is within a selected convergence threshold with respect to the desired customer service level; and

maintaining an inventory level responsive to said optimized inventory level.

13. The method of claim 12, further comprising interfacing with a user interface.

14. The method of claim 13, further comprising interfacing a processor with the user interface to determine the optimized inventory level.

15. The method of claim 14, further comprising storing data in a memory to be used by the processor to determine the optimized inventory level.

16. A computer readable storage medium including a set of instructions that causes a computer to perform the following steps:

interfacing a user interface with a processor

storing data on a memory to be used by the processor to execute an algorithm;

executing the algorithm on the processor to determine an optimized inventory level, the algorithm comprising the steps of;

selecting a desired customer service level;

obtaining at least one characteristic of a part repair lead-time distribution, wherein the at least one characteristic is a mean μ and

a variance σ

of the part repair lead-time distribution;

using the computer readable storage medium on a computer to compute a proposed inventory level based on said at least one characteristic, wherein computing a proposed inventory level includes recomputing a probability term β

having a distribution reflected by a difference term Δ

_β

and calculating the proposed inventory level as I=A·

(R−

W)−

μ

+Δ

_β

·

σ

, wherein I is the proposed inventory level, A is a part arrival value, R is a maximum repair time and W is a desired turnaround time window;

determining a calculated customer service level corresponding to the proposed inventory level;

comparing the calculated customer service level with the desired customer service level; and

selecting the proposed inventory level as the optimized inventory level when the calculated customer service level is within a selected convergence threshold with respect to the desired customer service level.