Optimized Deployment of Parts in a Distribution Network

• US 20080040183A1
• Filed: 06/25/2007
• Published: 02/14/2008
• Est. Priority Date: 10/26/2000
• Status: Active Grant

• Current Assignee: Blue Yonder Group, Inc. (Panasonic Holdings Corporation)
• Original Assignee: JDA Technologies US, Inc. (Panasonic Holdings Corporation)
• Inventors: Bakkalbasi, Omer, Birjandi, Rosa
• Granted Patent: US 7,594,601 B2
• Time in Patent Office: Days
• US Class Current: 705/8
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

A method for deploying parts is disclosed. Locations that include supply locations and demand locations are defined. A supply location supplies parts to a demand location. A demand is computed for each part at each location. An availability lead-time is estimated for each part at each location. A lead-time demand is computed for each part at each location using the availability lead-times for the part. A stock level is computed for each part at each location. A completely filled demand is determined from the lead-time demands and the stock levels, and a partially filled demand is determined from the lead-time demands and the stock levels. A coverage function for the parts at the locations is generated from the completely filled demand and the partially filled demand.

Claims

1. A method for deploying parts, comprising:

defining a plurality of locations comprising a plurality of supply locations and a plurality of demand locations, a supply location being operable to supply a plurality of parts to a demand location;

computing a demand for each part at each location;

estimating an availability lead-time for each part at each location;

computing a lead-time demand for each part at each location using the availability lead-times for the part;

computing a stock level for each part at each location;

determining a completely filled demand from the lead-time demands and the stock levels;

determining a partially filled demand from the lead-time demands and the stock levels; and

generating a coverage function for the parts at the locations from the completely filled demand and the partially filled demand.

2. The method of claim 1, further comprising:

optimizing the coverage function; and

determining an optimal deployment of the parts at the locations according to the optimized coverage function.

3. The method of claim 1, further comprising:

determining a completely backordered demand from the lead-time demands and the stock values;

determining a partially backordered demand from the lead-time demands and the stock values;

generating a backorder function for the parts at the locations from the completely back ordered demand and the partially backordered demand;

minimizing the backorder function; and

determining an optimal deployment of the parts at the locations according to the minimized backorder function.

4. The method of claim 1, further comprising:

generating a cost function for the parts at the locations;

minimizing the cost function; and

determining an optimal deployment of the parts at the locations according to the minimized cost function.

5. The method of claim 1, wherein computing the lead-time demand for a part at a location comprising a demand location comprises:

calculating a probability that a supply location can supply the part to the demand location;

computing a replenishment lead-time at the demand location according to the probability; and

computing the lead-time demand at the demand location from the demand at the demand location and the replenishment lead-time at the demand location.

6. The method of claim 1, wherein computing the lead-time demand for a part at a location comprises:

receiving an ordered list comprising at least a subset of the supply locations;

repeating the following for each supply location of the ordered list;

calculating a probability that a supply location supplies the part to the demand location, given that no other supply location has supplied the part; and

selecting the next supply location of the ordered list; and

estimating the availability lead-time at the location from the calculated probabilities.

7. The method of claim 1, wherein estimating the availability lead-time for a part at a location comprising a target demand location comprises:

estimating an availability lead-time for the part at a supply endpoint; and

repeating the following until the target demand location is reached;

estimating an availability lead-time for the part at a supply location; and

estimating a replenishment lead-time for the part at a demand location according to the availability lead-time for the part at the supply location, the supply location operable to supply the part to the demand location.

8. The method of claim 1, wherein computing the demand for a part at a location comprising a supply location comprises:

calculating a demand at a demand location operable to receive the part from the supply location;

calculating a dependent demand at the supply location according to the demand at the demand location;

calculating an independent demand at the supply location; and

computing the demand at the supply location from the dependent demand and the independent demand.

9. The method of claim 1, wherein computing the demand for a part at a location comprising a supply location comprises:

calculating a demand at a demand location operable to receive the part from the supply location;

establishing a probability of repairing the part at the demand location; and

determining the demand at the supply location according to the demand at the demand location and the probability of repairing the part at the demand location.

10. The method of claim 1, wherein computing the demand for a part at a location comprising a target supply location comprises:

calculating a demand at a demand endpoint; and

repeating the following until the target supply location is reached;

calculating a demand at a demand location; and

calculating a demand at a supply location operable to supply the part to the demand location according to the demand at the demand location.

11. Logic embodied in a computer-readable medium and when executed by a computer operable to:

define a plurality of locations comprising a plurality of supply locations and a plurality of demand locations, a supply location being operable to supply a plurality of parts to a demand location;

compute a demand for each part at each location;

estimate an availability lead-time for each part at each location;

compute a lead-time demand for each part at each location using the availability lead-times for the part;

generate a completely filled demand from the lead-time demands and the stock levels;

generate a partially filled demand from the lead-time demands and the stock levels; and

generate a coverage function for the parts at the locations from the completely filled demand and the partially filled demand.

12. The logic of claim 11, further operable to:

optimize the coverage function;

determine an optimal deployment of the parts at the locations according to the optimized coverage function; and

compute a stock level for each part at each location.

13. The logic of claim 11, further operable to:

determine a completely backordered demand from the lead-time demands and the stock values;

determine a partially backordered demand from the lead-time demands and the stock values;

generate a backorder function for the parts at the locations from the completely back ordered demand and the partially backordered demand;

minimize the backorder function; and

determine an optimal deployment of the parts at the locations according to the minimized backorder function.

14. The logic of claim 11, further operable to:

generate a cost function for the parts at the locations;

minimize the cost function; and

determine an optimal deployment of the parts at the locations according to the minimized cost function.

15. The logic of claim 11, wherein the logic is operable to compute the lead-time demand for a part at a location comprising a demand location by:

calculating a probability that a supply location can supply the part to the demand location;

computing a replenishment lead-time at the demand location according to the probability; and

computing the lead-time demand at the demand location from the demand at the demand location and the replenishment lead-time at the demand location.

16. The logic of claim 11, wherein the logic is operable to compute the lead-time demand for a part at a location by:

receiving an ordered list comprising at least a subset of the supply locations;

repeating the following for each supply location of the ordered list;

calculating a probability that a supply location supplies the part to the demand location, given that no other supply location has supplied the part; and

selecting the next supply location of the ordered list; and

estimating the availability lead-time at the location from the calculated probabilities.

17. The logic of claim 11, wherein the logic is operable to estimate the availability lead-time for a part at a location comprising a target demand location by:

estimating an availability lead-time for the part at a supply endpoint; and

repeating the following until the target demand location is reached;

estimating an availability lead-time for the part at a supply location; and

estimating an replenishment lead-time for the part at a demand location according to the availability lead-time for the part at the supply location, the supply location operable to supply the part to the demand location.

18. The logic of claim 11, wherein the logic is operable to compute the demand for a part at a location comprising a supply location by:

calculating a demand at a demand location operable to receive the part from the supply location;

calculating a dependent demand at the supply location according to the demand at the demand location;

calculating an independent demand at the supply location; and

computing the demand at the supply location from the dependent demand and the independent demand.

19. The logic of claim 11, wherein the logic is operable to compute the demand for a part at a location comprising a supply location by:

calculating a demand at a demand location operable to receive the part from the supply location;

establishing a probability of repairing the part at the demand location; and

determining the demand at a location according to the demand at the demand location for the location and the probability of repairing the part at the demand location.

20. The logic of claim 11, wherein the logic is operable to compute the demand for a part at a location comprising a target supply location by:

calculating a demand at a demand endpoint; and

repeating the following until the target supply location is reached;

calculating a demand at a demand location; and

calculating a demand at a supply location operable to supply the part to the demand location according to the demand at the demand location.

21. A system for deploying parts, comprising:

means for defining a plurality of locations comprising a plurality of supply locations and a plurality of demand locations, a supply location being operable to supply a plurality of parts to a demand location;

means for computing a demand for each part at each location;

means for estimating an availability lead-time for each part at each location;

means for computing a lead-time demand for each part at each location using the availability lead-times for the part;

means for generating a completely filled demand from the lead-time demands and the stock levels to be determined as a result of an optimization;

means for generating a partially filled demand from the lead-time demands and the stock levels; and

means for generating a coverage function for the parts at the locations from the completely filled demand and the partially filled demand.

22. A method for deploying parts, comprising:

defining a plurality of locations comprising a plurality of supply locations and a plurality of demand locations, a supply location being operable to supply a part to a demand location;

computing a demand for the part at each location by calculating a demand at a demand location operable to receive the part from a supply location, calculating a dependent demand at the supply location according to the demand at the demand location, calculating an independent demand at the supply location, and computing the demand at the supply location from the dependent demand and the independent demand;

estimating a lead-time demand of the part at each location by receiving an ordered list comprising at least a subset of the supply locations, and repeating the following for each supply location of the ordered list;

calculating a probability that a supply location supplies the part to the demand location, given that no other supply location has supplied the part; and

selecting the next supply location of the ordered list;

estimating the lead-time demand at the demand location from the calculated probabilities;

generating a completely filled demand from the demands and the lead-time demands;

generating a partially filled demand from the demands and the lead-time demands;

generating a coverage function for the part at the locations from the completely filled demand and the partially filled demand, the coverage function describing an expected backorder of the part at the locations;

minimizing the coverage function; and

determining an optimal deployment of the part at the locations according to the minimized coverage function.