Optimized deployment of parts in a distribution network

• US 7,672,867 B2
• Filed: 10/22/2007
• Issued: 03/02/2010
• Est. Priority Date: 10/26/2000
• Status: Expired due to Fees

• Current Assignee: Blue Yonder Group, Inc. (Panasonic Holdings Corporation)
• Original Assignee: i2 Technologies US Incorporated (Panasonic Holdings Corporation)
• Inventors: Birjandi, Rosa H., Bakkalbasi, Omer
• Primary Examiner(s): RUDY, ANDREW J
• Application Number:
  US11/876,210
• Publication Number:
  US 20080046309A1
• Time in Patent Office: 862 Days
• Field of Search: 705/10, 705/28, 705/7, 700/99, 700/106
• US Class Current: 705/7.31
• 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 computer-implemented method for deploying parts in a distribution network, comprising:

defining, by a computer, a plurality of locations in the distribution network comprising a plurality of supply locations and a plurality of demand locations, each supply location configured to supply a plurality of parts to a demand location;

calculating, by the computer, a demand for each part at each location;

estimating, by the computer, an availability lead-time for each part at each location;

calculating, by the computer, a lead-time demand for each part at each location using the availability lead-times for the part;

calculating, by the computer, a stock level for each part at each location;

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

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

generating, by the computer, 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 each location 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;

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

calculating 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 configured 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 configured 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

calculating 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 configured 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 configured to supply the part to the demand location according to the demand at the demand location.