Method and System for Generating Supplier Capacity Requirements

• US 20150100370A1
• Filed: 10/08/2013
• Published: 04/09/2015
• Est. Priority Date: 10/08/2013
• Status: Abandoned Application

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Fradkin, Yakov M., Puskorius, Gintaras Vincent, Tappeta, Ravindra Venkata
• Application Number:
  US14/048,556
• Publication Number:
  US 20150100370A1
• Time in Patent Office: Days
• US Class Current: 705/7.25
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0875 Itemisation or classification of parts, supplies or services, e.g. bill of materials

Abstract

One or more embodiments include a computer-implemented method or system for generating part volumes necessary to assemble all vehicles of a vehicle product line for a predetermined time period. The method or system being configured to receive a product definition representing valid configurations for a product. The products may include feature families with mutually exclusive features. The method or system also receives a feature forecast rate or sales forecast rate that may be an aggregated demand. The method or system may further receive a bill of material for the product. The method or system may generate a forecasted order that is a quantity of each configuration by interacting the feature forecast rate and the product definition. The method or system may further generate a part volume necessary to assemble the product by interacting the quantity of each configuration with a product bill of material.

Claims

1. A forecasting method comprising:

receiving a product definition representing valid configurations for a product;

receiving a forecast for total sales quantity and feature rates;

receiving a bill of material for the product;

generating a forecasted order by interacting the feature forecast rate with the product definition; and

generating the quantity of all parts necessary to assemble the product by interacting the forecasted order with the bill of material.

2. The method of claim 1, wherein the forecasted order is generated by mapping the feature forecast rate against the product definition, wherein the forecasted order results in assigning nonnegative quantities to all features and configurations of which the product definition is comprised.

3. The method of claim 2 wherein the product definition is represented using a binary super-configuration matrix that includes a bit corresponding to every configurable feature available in the product.

4. The method of claim 3, wherein the binary super-configuration is configured such that each row includes at least one non-zero bit from each family.

5. The method of claim 3, wherein each row in the binary super-configuration matrix includes exactly one non-zero bit from each family.

6. The method of claim 2, wherein the forecasted order is generated such as to avoid as much as practically possible assigning zero quantities to any features and configurations of which the product definition is comprised.

7. The method of claim 4 wherein the forecasted order is calculated based on a ratio of a final quantity of a designated feature from an associated family in a designated super-configuration to a final calculated quantity of the feature from the family in the super-configuration.

8. The method of claim 7 wherein the forecasted order is calculated based on a minimum value of a summation over possible values for the features from associated families for each super-configuration of the final calculated quantity multiplied by a logarithm of the ratio.

9. The method of claim 4, wherein the forecasted order is calculated using the following equation:

10. The method of claim 9, wherein the equation is implemented using Sequential Quadratic Programming.

11. The method of claim 2, wherein the step of generating a forecasted order further involves relaxing the feature forecast rates if the forecasted rates are determined to be inconsistent with respect to the product definition.

12. The method of claim 2, wherein the forecasted order is calculated using the following equation:

13. The method of claim 2, wherein each super-configuration encodes one or more configurations.

14. The method of claim 3, wherein a part volume is generated using the following equation:

15. The method of claim 12, wherein the value V_hk is calculated using the following equation:

16. The method of claim 12, wherein the value (V_hk) is calculated using the following equation:

17. The method of claim 1, wherein the feature forecast rate is an aggregated demand.

18. The method of claim 1, wherein the forecasted order specifies the quantity of each feature in each configuration of the product.

19. A system for forecasting a quantity of parts necessary to assemble all vehicles of a vehicle product, comprising:

a processor configured to;

receive a product definition representing valid configurations for a product, wherein the products include feature families with mutually exclusive features;

receive a forecast for total sales quantity and feature rates, wherein the forecasted rate is an aggregated demand;

receive a bill of material for the product;

generate a forecasted order specifying the quantity of each feature in each configuration of the product by interacting the feature forecast rate with the product definition; and

generate the quantity of all parts necessary to assemble the vehicle product in the forecasted order by interacting the quantity of each configuration in the forecasted order with a product bill of material.

20. A method for forecasting a quantity of parts necessary to assemble all vehicles of a vehicle product, comprising:

receiving a product definition representing valid configurations for a product, wherein the products include feature families with mutually exclusive features;

receiving a forecast for total sales quantity and feature rates, wherein the forecasted rate is an aggregated demand;

receiving a bill of material for the product;

generating a forecasted order specifying the quantity of each feature in each configuration of the product by interacting the feature forecast rate with the product definition; and

generating the quantity of all parts necessary to assemble the vehicle product in the forecasted order by interacting the quantity of each configuration in the forecasted order with a product bill of material.