Associated systems and methods for improving planning, scheduling, and supply chain management

• US 20060235557A1
• Filed: 03/06/2006
• Published: 10/19/2006
• Est. Priority Date: 10/11/2002
• Status: Active Grant

• Current Assignee: Invistics Corp. (Wolters Kluwer Nv)
• Original Assignee: Invistics Corp. (Wolters Kluwer Nv)
• Inventors: McGinnis, Leon, Knight, Thomas, McDonnell, Patrick, Bishop, John, Graves, Steven, Guan, Sichong, Sulka, Brian, Rosenfield, Donald, Jennings, Otis B.
• Granted Patent: US 7,499,766 B2
• Time in Patent Office: Days
• US Class Current: 700/103
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

The invention relates to systems and methods for improving planning, scheduling, and supply chain management. Embodiments of the invention can provide some or all of the following: improved systems and methods for determining an optimal lot size, improved systems and methods for determining optimal WIP levels, improved systems and methods for an inventory advisor module, improved systems and methods for integrating functionality of a lot sizer and WIP module and an inventory module, improved systems and methods for implementing multi-echelon inventory analysis, and improved systems and methods for partitioning planning information.

Claims

1. A computer-implemented method for determining an optimal lot size for multiple items in a flow path, comprising:

(a) receiving a selection of a lot size for each item in the flow path;

(b) based at least in part on the selected lot sizes, estimating a respective cycle time for the items in the flow path;

(c) based at least in part on the respective cycle times, determining an aggregate cycle time for the flow path, wherein the aggregate cycle time comprises at least one search direction;

(d) based in part on at least the aggregate cycle time, determining whether to modify a lot size for a particular item to optimize the aggregate cycle time; and

(e) if a determination is made to modify a lot size for a particular item, repeating elements (a)-(d) as needed by applying an iterative algorithm based in part on Powell'"'"'s method.

2. The computer-implemented method of claim 1, wherein the iterative algorithm based in part on Powell'"'"'s method can be implemented with at least one gradient search technique.

3. The computer-implemented method of claim 1, wherein the iterative algorithm based in part on Powell'"'"'s method can be constrained by at least one variable associated with an item in the flow path.

4. The computer-implemented method of claim 1, wherein the iterative algorithm based in part on Powell'"'"'s method can be constrained by at least one user selected variable associated with an item in the flow path.

5. The computer-implemented method of claim 1, wherein receiving a selection of a lot size for each item in the flow path comprises receiving a user input of a lot size for at least one item in the flow path.

6. The computer-implemented method of claim 1, wherein a ranking criteria can be determined for a plurality of items in the flow path.

7. The computer-implemented method of claim 6, wherein the ranking criteria is selected from a group comprising at least one of the following:

amount of influence a lot size of a particular item has on overall performance;

or significance of a setup quantity of a particular product with respect to a workstation associated with the product.

8. The computer-implemented method of claim 6, wherein the plurality of items with ranking criteria are optimized in a priority order based on the ranking criteria.

9. A computer-implemented method for determining an optimal work in progress level for multiple items in a flow path, comprising:

(a) providing a user interface capable of outputting a throughput for items in the flow path;

(b) receiving a selection of a policy for at least one item in the flow path;

(c) receiving a selected work in progress level for the policy;

(d) based at least in part on the selected policy and work in progress level, determining the throughput for each respective item in the flow path;

(e) outputting via the user interface an aggregate throughput associated with the multiple items in the flow path;

(f) based in part on at least the aggregate throughput, determining whether to modify a work in progress level for a particular item to optimize the aggregate throughput; and

(g) if a determination is made to modify a work in progress level for a particular item, repeating elements (c)-(f) as needed.

10. The computer-implemented method of claim 9, further comprising:

(h) outputting via the user interface a revised aggregate throughput associated with the multiple items in the flow path, wherein the revised aggregate throughput is based in part on at least a modified work in progress level for a particular item.

11. The computer-implemented method of claim 9, wherein the aggregate throughput comprises an intersection of a plurality of curves associated with a respective throughput for a respective item in the flow path.

12. The computer-implemented method of claim 9, wherein if a determination is made not to modify a work in progress level for a particular item, then the selected policy and work in progress level can be transmitted for implementation on the corresponding item in the flow path.

13. The computer-implemented method of claim 9, wherein determining a throughput for each respective item in the flowpath comprises applying discrete event simulation.

14. The computer-implemented method of claim 9, wherein outputting via the user interface an aggregate throughput associated with the multiple items in the flow path comprises a graphical representation of throughput versus at least one variable associated with the policy.

15. The computer-implemented method of claim 14, wherein a user selection of a particular graphical representation can permit a user to modify a work in progress level associated with the policy.

16. The computer-implemented method of claim 9, wherein outputting via the user interface an aggregate throughput associated with the multiple items in the flow path comprises a plurality of indicia capable of distinguishing between performance levels associated with different selected policies and respective work in progress levels.

17. The computer-implemented method of claim 16, wherein a user selection of a particular indicia can permit a user to modify a work in progress level associated with a particular policy.

18. A computer-implemented method for providing an exchange curve for an item in a flow path, wherein at least one constraint to the exchange curve can be represented, comprising:

providing a user interface capable of outputting an exchange curve;

receiving a user selection of a demand and a lead time for the item in the flow path;

based in part on at least a user selection, determining a distribution to apply to the selected demand and lead time for the item in the flow path;

applying the distribution to the selected demand and lead time for the item in the flow path; and

based in part on at least the distribution, outputting an exchange curve via the user interface.

19. The computer-implemented method of claim 18, wherein the exchange curve is represented on a logarithmic scale.

20. The computer-implemented method of claim 18, wherein the distribution can comprise at least one of the following:

a normal distribution, a gamma distribution, or a compound Bernoulli distribution.

21. The computer-implemented method of claim 18, wherein determining a distribution to apply to the selected demand and lead time for the item in the flow path comprises applying at least one statistical technique to the user selection of data associated with the item in the flow path.

22. The computer-implemented method of claim 21, wherein a statistical technique can comprise at least one of the following:

a mean, or a standard deviation.

23. A computer-implemented method for determining lot sizes for multiple items in a flow path, comprising, comprising:

receiving at least one selected lot size for an item in the flow path;

based at least in part on a selected lot size, determining a cycle time for the item using at least one model;

based at least in part on the selected lot size and cycle time for the item, determine an inventory capable of supporting at least one performance goal;

based at least in part on the cycle time and inventory, determining a cost for the policy; and

based at least in part on the cost of the policy, determining whether to modify the selected lot size.

24. The computer-implemented method of claim 23, wherein the model comprises at least one of the following:

a queueing model, or discrete event simulation.

25. The computer-implemented method of claim 23, wherein if the selected lot size is not modified, then the policy is implemented with the flow path.

26. The computer-implemented method of claim 23, wherein if the selected lot size is modified, then based at least in part on the modified selected lot size, a new cycle time determined for the item using the model.

27. A computer-implemented method for optimizing a multi-echelon inventory system, wherein the multi-echelon inventory system comprises multiple flow paths, comprising:

receiving inventory data associated with multiple flow paths;

based at least in part on the inventory data, determining at least one sub-problem;

based at least in part on the sub-problem, determining a data structure associated with each sub-problem;

based at least in part on the data structure for each sub-problem, determining a solution to each sub-problem; and

based at least in part on the sub-problem solutions, determining an initial optimization solution for the multi-echelon inventory system.

28. The computer-implemented method of claim 27, further comprising:

applying an iterative process to modify the optimization solution for the multi-echelon inventory system.

29. The computer-implemented method of claim 28, wherein the iterative process comprises discrete event simulation.

30. The computer-implemented method of claim 27, further comprising:

providing a user interface capable of permitting a user to modify the optimization solution.

32. The computer-implemented method of claim 27, wherein a portion of the set of products are unassigned to at least one group.

33. The computer-implemented method of claim 27, wherein the unassigned portion of the set of products are evaluated against at least one of the following:

at least one new characteristic, at least one new group, or at least one new rule.

34. The computer-implemented method of claim 27, further comprising:

defining either at least one new characteristic, group, or rule;

wherein the set of unassigned products is evaluated until all of the set of products are assigned to at least one group.

31. A computer-implemented method for partitioning a plurality of products, comprising:

identifying a set of products;

defining an initial set of characteristics associated with at least some of the products;

evaluating the set of products against the initial set of characteristics, wherein if a particular product comprises a particular characteristic, then the particular product can be rated for the particular characteristic;

defining a plurality of set of groups;

defining a set of initial rules;

evaluating the set of initial rules against the set of products and set of initial characteristics, wherein particular products rated with a particular characteristic can be assigned to a particular group based at least in part on a rule in the set of initial rules, and wherein the set of products is evaluated against the set of initial rules until at least some of the set of products are assigned to at least one group.

35. A system for determining an optimal lot size for multiple items in a flow path, comprising:

a lot sizer module adapted to;

(a) receive a selection of a lot size for each item in the flow path;

(b) based at least in part on the selected lot sizes, estimate a respective cycle time for the items in the flow path;

(c) based at least in part on the respective cycle times, determine an aggregate cycle time for the flow path, wherein the aggregate cycle time comprises at least one search direction;

(d) based in part on at least the aggregate cycle time, determine whether to modify a lot size for a particular item to optimize the aggregate cycle time; and

(e) if a determination is made to modify a lot size for a particular item, repeat elements (a)-(d) as needed by applying an iterative algorithm based in part on Powell'"'"'s method.

36. A system for determining an optimal work in progress level for multiple items in a flow path, comprising:

a work in progress estimator module adapted to;

(a) provide a user interface capable of outputting a throughput for items in the flow path;

(b) receive a selection of a policy for at least one item in the flow path;

(c) receive a selected work in progress level for the policy;

(d) based at least in part on the selected policy and work in progress level, determine the throughput for each respective item in the flow path;

(e) output via the user interface an aggregate throughput associated with the multiple items in the flow path;

(f) based in part on at least the aggregate throughput, determine whether to modify a work in progress level for a particular item to optimize the aggregate throughput; and

(g) if a determination is made to modify a work in progress level for a particular item, repeat elements (c)-(f) as needed.

37. A system for providing an exchange curve for an item in a flow path, wherein at least one constraint to the exchange curve can be represented, comprising:

an inventory advisor module adapted to;

provide a user interface capable of outputting an exchange curve;

receive a user selection of a demand and a lead time for the item in the flow path;

based in part on at least a user selection, determine a distribution to apply to the selected demand and lead time for the item in the flow path;

apply the distribution to the selected demand and lead time for the item in the flow path; and

based in part on at least the distribution, output an exchange curve via the user interface.

38. A system for determining lot sizes for multiple items in a flow path, comprising:

a lot sizer and work in progress estimator module adapted to;

receive at least one selected lot size for an item in the flow path;

based at least in part on a selected lot size, determine a cycle time for the item using at least one model;

based at least in part on the selected lot size and cycle time for the item, determine an inventory capable of supporting at least one performance goal; and

based at least in part on the cycle time and inventory, determine a cost for the policy; and

based at least in part on the cost of the policy, determine whether to modify the selected lot size.

39. A system for optimizing a multi-echelon inventory system, wherein the multi-echelon inventory system comprises multiple flow paths, comprising:

a multi-echelon inventory advisor module adapted to;

receive inventory data associated with multiple flow paths;

based at least in part on the inventory data, determine at least one sub-problem;

based at least in part on the sub-problem, determine a data structure associated with each sub-problem;

based at least in part on the data structure for each sub-problem, determine a solution to each sub-problem; and

based at least in part on the sub-problem solutions, determine an initial optimization solution for the multi-echelon inventory system,

40. A system for partitioning a plurality of products, comprising:

an inventory advisor module adapted to;

identify a set of products;

define an initial set of characteristics associated with at least some of the products;

evaluate the set of products against the initial set of characteristics, wherein if a particular product comprises a particular characteristic, then the particular product can be rated for the particular characteristic;

define a plurality of set of groups;

define a set of initial rules; and

evaluate the set of initial rules against the set of products and set of initial characteristics, wherein particular products rated with a particular characteristic can be assigned to a particular group based at least in part on a rule in the set of initial rules, and wherein the set of products is evaluated against the set of initial rules until at least some of the set of products are assigned to at least one group