Optimizing resource plans

• US 20030208392A1
• Filed: 11/05/2002
• Published: 11/06/2003
• Est. Priority Date: 10/27/2000
• Status: Abandoned Application

• Current Assignee: JDA Software Group Incorporated (Panasonic Holdings Corporation)
• Original Assignee: Manugistics Inc (Panasonic Holdings Corporation)
• Inventors: MacMillan, Robert, Joshi, Salil, Shekar, Konanur C., Greamo, Chris, Bongartz, Ingrid, Hooks, Michael
• Application Number:
  US10/287,774
• Publication Number:
  US 20030208392A1
• 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 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

The present invention relates to a master resource planning systems and related methods for optimizing resource plans across multiple networks. In particular, the present invention optimizes constrained resources across multiple networks and produces an optimized plan to allocate and coordinate the obtaining, shipping and procurement of limited resources based upon user-defined strategies and supplier/shipper preferences Aspects of the disclosure include creating planning data and planning rules. Planning data contains information regarding constrained resources in the multiple networks. Planning rules are based on user-defined strategies. Additional aspects include generating a plan based on the planning data and the planning rules and revising the plan in real-time. The generated plan optimally allocates the constrained resources according to the user-defined strategies. Certain embodiments disclosed herein employ pegging strategies for handling over and under availability of demanded resources among a variety of competing orders. Other certain embodiments disclosed herein optimize the procurement of resources needed to fulfill orders in part by taking into account limitations in shipping lag times, established transportation schedules, and carrier preferences.

Claims

1. A method for optimizing resource plans across a multi-location supply network, said network including locations for multiple supply points and at least one location for a demand point wherein said supply point provides supply items needed by said demand point according to said resource plans, said method comprising:

creating planning data, planning data containing information regarding constrained resources, said constrained resources including vessel scheduling information for transporting said supply items from said supply points to said demand point;

creating planning rules based on user-defined strategies, said planning rules identifying acceptable timeframes in which supplies of said supply items must arrive at said demand point in order to meet consumption dates for given orders;

generating a plan based on the planning data and the planning rules, wherein the plan optimally allocates the constrained resources according to the user-defined strategies, said plan providing required consumption dates of said supply items; and

revising the plan in real-time.

2. The method of claim 1, further comprising:

publishing the plan; and

implementing the plan by issuing commands in the multiple networks.

3. The method of claim 2, wherein the publishing step further comprises issuing one or more alerts.

4. The method of claim 1, wherein the plan includes orders for supply items from said supply points, and wherein said planning rules include shipping schedules for available shipping alternatives.

5. The method of claim 4, wherein said shipping alternatives comprise shipping routes for alternative shipping carriers.

6. The method of claim 5, wherein one of said alternative shipping carriers is designated as the preferred carrier.

7. The method of claim 5, wherein said alternative shipping carriers are prioritized such that in said plan more preferred carriers are selected over less preferred carriers when possible.

8. The method of claim 1, wherein the constrained resources include materials, capacities, inventories, transportation resources, and distribution resources.

9. The method of claim 1, wherein the revising step takes into account user inputs and real-time events including production breakdowns, distribution delays, and material shortages occurring within the multiple networks.

10. The method of claim 1, wherein the revising step further comprises revising said plan until said consumption dates can be met.

11. The method of claim 1, wherein the revising step further comprises:

validating the plan; and

repairing the plan.

12. The method of claim 1, wherein the generating step also considers one or more aggregate stock keeping units.

13. The method of claim 1, wherein the generating step uses one or more loading strategies.

14. The method of claim 13, wherein the one or more loading strategies include sequential loading, parallel loading, variable lead-time calculation, and just-in-time loading.

15. The method of claim 1, wherein the generating step considers one or more ship-complete orders.

16. The method of claim 1, wherein the generating step further comprises:

minimizing an excess, including an inventory excess and a supply excess.

17. The method of claim 16, wherein minimizing said excesses is accomplished by pegging said demands according to said planning rules.

18. The method of claim 16, wherein the dynamic factors include shipping calendars, receiving calendars, effectivity calendars, manufacturing availability calendars, and constraint settings.

19. A system for optimizing resource plans across a multi-location supply network, said network including locations for multiple supply points and at least one location for a demand point wherein said supply point provides supply items needed by said demand point according to said resource plans, said system comprising:

means for creating planning data, planning data containing information regarding constrained resources, said constrained resources including vessel scheduling information for transporting said supply items from said supply points to said demand point;

means for creating planning rules based on user-defined strategies, said planning rules identifying acceptable timeframes in which supplies of said supply items must arrive at said demand point in order to meet consumption dates for given orders;

means for generating a plan based on the planning data and the planning rules, wherein the plan optimally allocates the constrained resources according to the user-defined strategies, said plan providing required consumption dates of said supply items; and

means for revising the plan in real-time.

20. A computer program product comprising a computer useable medium having computer readable code embodied therein for optimizing resource plans across a multi-location supply network, said network including locations for multiple supply points and at least one location for a demand point wherein said supply point provides supply items needed by said demand point according to said resource plans, said code having instructions comprising:

creating planning data, planning data containing information regarding constrained resources, said constrained resources including vessel scheduling information for transporting said supply items from said supply points to said demand point;

creating planning rules based on user-defined strategies, said planning rules identifying acceptable timeframes in which supplies of said supply items must arrive at said demand point in order to meet consumption dates for given orders;

generating a plan based on the planning data and the planning rules, wherein the plan optimally allocates the constrained resources according to the user-defined strategies, said plan providing required consumption dates of said supply items; and

revising the plan in real-time.