Method for part procurement in a production system with constrained resources

• US 5,970,465 A
• Filed: 06/04/1997
• Issued: 10/19/1999
• Est. Priority Date: 10/05/1994
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Srinivasan, Ramesh, Lin, Grace Yuh-Jiun, Dietrich, Brenda Lynn
• Primary Examiner(s): Poinvil, Frantzy
• Application Number:
  US08/871,567
• Time in Patent Office: 867 Days
• Field of Search: 705/7, 705/8, 705/10, 705/28, 705/29, 364/468.05, 364/468.09, 364/468.13, 364/468.16
• US Class Current: 705/7.22
• 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 10/06314 Calendaring for a resource
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change

Abstract

A method for determining procurement for parts (P) in a production system having constraints comprising at least one of constrained resources (r_i) and known maximum demands (d_j). The method comprises two steps. Step 1 includes constructing a production planning decision space comprising independent sets of hyperplanes defined by decision variables (q_j) corresponding to product quantities for products (j). The constructing step subsumes steps of expressing a potential usage of part (p) as a linear combination of production quantities (q_j) based on bill of material usage rules; limiting the production quantities (q_j) so that each is less than or equal to the maximum demand quantity (d_j); and limiting the production quantities (q_i) so that the usage of each resource (r) is based on bill of material and bill of capacity usage rates less than or equal to the availability of that resource. For each part p, the second step includes locating a region in the decision space corresponding to a high level of usage of part (p).

Claims

1. A computer implemented process for determining procurement level for parts (P) in a production system having constraints comprising at least one of constrained resources (r) and known maximum demands d_j, comprising:

1) inputting to the computer, data including decision variables, production quantity, demand quantity, bill of material, bill of capacity and usage rate;

2) constructing in computer memory a production planning decision space consisting of independent sets of hyperplanes defined by decision variables q_j,t corresponding to production quantities for products (j), said constructing including the steps of;

a) expressing a potential usage of part (p) as a linear combination of production quantities (q_j);

b) limiting the production quantities (q_j) so that it is less than or equal to the maximum demand quantity (d_j);

and

c) limiting the production quantities (q_j) so that the usage of each other resource (r) based on multiple level bill of material and bill of capacity usage rates is less than or equal to the availability of that resource;

3) locating a region in the decision space corresponding to a high level of usage of part (p);

and

4) interactively displaying to a user candidate values in said decision space corresponding to the highest level of usage of part (p) so assist the user in deciding quantities of part (p) to procure necessary to enable achievement of the highest level of service, corresponding to the highest level of usage of part (p), while maintaining the lowest possible WIP and inventory on the basis of linear demand, resource, and supply constraining information.

2. A method according to claim 1, wherein the decision space is temporally expanded by the step of separating each decision variable q_j,t into a set of decision variables q_j,t according to a calendar mechanism to determine the quantity of activity j to do in a period t, said step further including

modifying the creation of said independent sets of hyperplanes by adding decision variables q_j,t corresponding to shipment of product, stock of materials, and scrapping of resources in each period;

and

expressing the demand for a product as demand quantities over time; and

determining the time based cost factors on backlogging demand and carrying material; and

expressing the availability of resources over time; and

constructing an objective function consisting of a plurality of objective function coefficients and associated decision variables q(_j,t), wherein said objective function rewards the shipment of products using a specific part(p) and penalizes holding or scrapping of part (p) or products using part(p); and

using said objective function to locate a region in the decision space corresponding to a high level of usage of part (p).

3. A method according to claim 2, wherein step 2) comprises:

a) expressing a potential usage of part (p) in period t as a linear combination of production quantities q_j ;

b) limiting the production quantities q_j so that a cumulative production through a period r is less than or equal to cumulative maximum demand quantity through period r;

and

c) limiting the production quantities q_j so that the usage of each other material or capacity resource (r) in a time period r based on bill of material and bill of capacity usage rates is less than or equal to the availability of that resource in time period r;

and

wherein step (2) further comprises locating a region in the decision space corresponding to a high level of usage of part (p) in period r.

4. A method according to claim 2, comprising the additional step of procuring parts in a period closest to the actual usage period for said parts consistent with the constraints of known available external supply.

5. A method according to claim 1, wherein the decision space is temporally expanded by the steps of:

(i) separating each decision variable q_j,t into a set of decision variables q_j,t according to a calendar mechanism to determine the quantity of activity i to do in a period t, said step further including

modifying the creation of said independent sets of hyperplanes by adding decision variables q_j,t corresponding to shipment of product, stock of materials, and scrapping of resources in each period; and

expressing the demand for a product as demand quantities over time; and

determining the time based cost factors on backlogging demand and carrying material; and

expressing the availability of resources over time; and

constructing an objective function consisting of a plurality of objective function coefficients and associated decision variables q.sub.(j,t), wherein said objective function rewards the shipment of products using a specific part(p) and penalizes holding or scrapping of part (p) or products using part (p); and

using said objective function to locate a region in the decision space corresponding to a high level of usage of part (p).

(ii) adjusting the hyperplane to represent non-zero manufacturing lead times.

6. A method according to claim 5 where the Bill of Material BOM is multi-level ensuring that unnecessary parts are not procured when a choice exists between procuring parts or using existing subassemblies.

7. A method according to claim 1, wherein the step of locating an optimal region in the decision space comprising a high level of usage further includes constructing a special objective function comprising objective function coefficients for each of the decision variables.

8. A machine suitable for determining procurement level for parts (P) in a production arrangement having constraints comprising at least one of constrained resources (r_i) and known maximum demands (d_j) the machine comprising:

1) means for inputting data comprising variables including decision variables, production quantity, demand quantity, bill of material, bill of capacity and usage rates;

2) means for creating a production planned decision space comprising independent sets of hyperplanes defined by decision variables q_j,t corresponding to product quantities for product (j), said means for creating comprising

a) expressing a potential usage of part p) in period t as a linear combination of production quantities (q(j))

b) limiting the production quantities q_j so that a cumulative production through a period r is less than or equal to cumulative maximum demand quantity through period r; and

c) limiting the production quantities q_j so that the usage of each other resource (r) based on multiple level bill of material and bill of capacity usage rates is less than or equal to the availability of that resource

and

3) means associated with each part (p) for locating a region in the decision space corresponding to the highest level of usage of part (p);

and

4) means for interactively displaying to a user candidate values in said decision space corresponding to the highest level of usage of part (p) to assist the user in deciding quantities of part (p) to procure necessary to enable achievement of the highest level of service, corresponding to the highest level of usage of part (p), while maintaining the lowest possible Work in Process WIP and inventory on the basis of linear demand, resource, and supply constraining information.

9. A machine according to claim 8 wherein the bill of materials comprises multiple levels ensuring that unnecessary parts are not procured when a choice exists between procuring parts or using existing subassemblies.