Methods and Systems for Dynamic Wrinkle Prediction

• US 20110202325A1
• Filed: 02/12/2010
• Published: 08/18/2011
• Est. Priority Date: 02/12/2010
• Status: Active Grant

• Current Assignee: Toyota Motor Corporation
• Original Assignee: Toyota Motor Engineering & Manufacturing North America Incorporated (Toyota Motor Corporation)
• Inventors: DeGrood, Kevin B.
• Granted Patent: US 8,428,920 B2
• Time in Patent Office: Days
• US Class Current: 703/6
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design

Abstract

Systems and methods for predicting a dynamic wrinkle property are provided. In one embodiment, a method of predicting a dynamic wrinkle property of a material for incorporation with an upholstered article includes selecting a plurality of material property categories and determining a material property for each selected material property category of a material. A dynamic wrinkle factor is assigned for each material property category based at least in part on the material property associated with the material property category. A dynamic wrinkle weight value is applied to each dynamic wrinkle factor to generate a weighted dynamic wrinkle factor for each material property category. The method further includes determining a predicted dynamic wrinkle score based at least in part on the weighted dynamic wrinkle factors and altering one or more material properties of the material if the predicted dynamic wrinkle score is below a benchmark value.

Claims

1. A method of predicting a dynamic wrinkle property of a material for incorporation with an upholstered article comprising:

selecting a plurality of material property categories;

determining a material property for each selected material property category of a material;

assigning a dynamic wrinkle factor for each material property category based at least in part on the material property associated with the material property category;

applying a dynamic wrinkle weight value to each dynamic wrinkle factor to generate a weighted dynamic wrinkle factor for each material property category;

determining a predicted dynamic wrinkle score based at least in part on the weighted dynamic wrinkle factors; and

altering one or more material properties of the material if the predicted dynamic wrinkle score is below a benchmark value.

2. The method of claim 1 wherein determining the predicted dynamic wrinkle score further comprises summing the weighted dynamic wrinkle factors.

3. The method of claim 1 wherein the dynamic wrinkle factors are within a dynamic wrinkle factor range.

4. The method of claim 1 wherein a summation of the dynamic wrinkle weight values is equal to 1.0.

5. The method of claim 1 wherein the dynamic wrinkle factor for each material property category corresponds to a positive, neutral or negative dynamic wrinkle performance based on historical data.

6. The method of claim 1 wherein the material property categories comprise two or more of the following:

seat pattern design, seat foam hardness, seat foam density, material color, material construction, fabric scrim, pile, lamination thickness, lamination density, constant load set, constant load elongation, Taber abrasion, circular modulus, bending length, and stiffness/softness.

7. The method of claim 1 wherein the material property categories include:

seat pattern design, seat foam hardness, seat foam density, material color, material construction, fabric scrim, pile, lamination thickness, lamination density, constant load set, constant load elongation, Taber abrasion, circular modulus, bending length, and stiffness/softness.

8. A method of designing a material of an upholstered article comprising:

providing a material;

predicting a dynamic wrinkle property of the material by performing a dynamic wrinkle property prediction analysis, the dynamic wrinkle property prediction analysis comprising;

selecting two or more material property categories from a plurality of material property categories associated with the material;

determining a material property for each selected material property category;

assigning a dynamic wrinkle factor for each selected material property category based at least in part on the material property associated with the selected material property category;

applying a dynamic wrinkle weight value to each dynamic wrinkle factor to generate a weighted dynamic wrinkle factor for each selected material property category; and

determining a predicted dynamic wrinkle score based at least in part on the weighted dynamic wrinkle factors; and

comparing the predicted dynamic wrinkle score with a predicted dynamic wrinkle score benchmark value;

altering one or more material properties and performing the dynamic wrinkle property prediction analysis for a material with the altered material properties if the predicted dynamic wrinkle score is less than the predicted dynamic wrinkle score benchmark value; and

selecting the material if the predicted dynamic wrinkle score is greater than or equal to the predicted dynamic wrinkle score benchmark value.

9. The method of claim 8 further comprising performing a dynamic wrinkle evaluation test of the selected material.

10. The method of claim 8 wherein determining the predicted dynamic wrinkle score further comprises summing the weighted dynamic wrinkle factors.

11. The method of claim 8 wherein the dynamic wrinkle factors are within a dynamic wrinkle factor range.

12. The method of claim 8 wherein a summation of the dynamic wrinkle weight values is equal to 1.0.

13. The method of claim 8 wherein the dynamic wrinkle factor for each material property category corresponds to a positive, neutral or negative dynamic wrinkle performance based on historical data.

14. The method of claim 8 wherein the material property categories comprise:

seat pattern design, seat foam hardness, seat foam density, material color, material construction, fabric scrim, pile, lamination thickness, lamination density, constant load set, constant load elongation, Taber abrasion, circular modulus, bending length, and stiffness/softness.

15. A dynamic wrinkle prediction system comprising:

a processor;

a graphical display; and

a memory, wherein the memory comprises a set of executable instructions operable to cause the processor to;

receive a plurality of material properties associated with a material, the plurality of material properties corresponding to a plurality of material property categories;

assign a dynamic wrinkle factor for each material property category based at least in part on the material property associated with the material property category;

apply a dynamic wrinkle weight value to each dynamic wrinkle factor to generate a weighted dynamic wrinkle factor for each material property category;

determine a predicted dynamic wrinkle score based at least in part on the weighted dynamic wrinkle factors; and

display the predicted dynamic wrinkle score on the graphical display.

16. The dynamic wrinkle prediction system of claim 15 wherein determining the predicted dynamic wrinkle score further comprises summing the weighted dynamic wrinkle factors.

17. The dynamic wrinkle prediction system of claim 15 wherein the dynamic wrinkle factors are within a dynamic wrinkle factor range.

18. The dynamic wrinkle prediction system of claim 15 wherein a summation of the dynamic wrinkle weight values is equal to 1.0.

19. The dynamic wrinkle prediction system of claim 15 wherein the dynamic wrinkle factor for each material property category corresponds to a positive, neutral or negative dynamic wrinkle performance based on historical data.

20. The dynamic wrinkle prediction system of claim 15 wherein the material property categories include:

seat pattern design, seat foam hardness, seat foam density, material color, material construction, fabric scrim, pile, lamination thickness, lamination density, constant load set, constant load elongation, Taber abrasion, circular modulus, bending length, and stiffness/softness.