Weldability prediction and recommendation systems and methods

• US 8,706,282 B2
• Filed: 01/12/2010
• Issued: 04/22/2014
• Est. Priority Date: 01/12/2010
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Sohmshetty, Raja Shekar, Coon, Theodore, Subramanian, Saravanan, Xia, Zhiyong Cedric
• Primary Examiner(s): VON BUHR, MARIA N
• Application Number:
  US12/685,886
• Publication Number:
  US 20110172796A1
• Time in Patent Office: 1,561 Days
• Field of Search: 700 28- 36, 700 95- 98, 700103-105, 700108-110, 219/136, 219/137.R, 706/21, 706 45- 48, 706/903, 706/904, 706/919, 706/920, 703/1, 703/2
• US Class Current: 700/103
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 2219/32101 CASE based process planning, using older, known case
• CPC Class Codes: G05B 2219/32153 Exchange data between user, cad, caq, nc, capp
• CPC Class Codes: G05B 2219/45135 Welding
• CPC Class Codes: G06F 2113/24 Sheet material
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

In one or more embodiments, a weldability of a stack-up for use in vehicle part production may be determined. The determination may include receiving general stack-up information, welding standards data for forming a stack-up, and one or more inputs defining one or more stack-up design variables. Additionally, standardized stack-up information may be generated based on the general stack-up information, the one or more design variables, and the welding standards data. Furthermore, historical welding data may be received for predicting a weldability of the stack-up. Predictive logic may be applied to the standardized stack-up information based on the historical welding data to obtain one or more weldability predictions for the stack-up. The one or more weldability predictions may be transmitted for use in vehicle part production.

Claims

1. A computer-implemented method for determining a weldability of a plurality of layers of materials forming a stack-up for use in vehicle part production, the computer-implemented method comprising:

receiving general stack-up information;

receiving welding standards data for welding together a plurality of materials forming a stack-up;

receiving one or more inputs defining one or more design variables of the one or more stack-ups;

generating standardized stack-up information based on the general stack-up information, the one or more design variables, and the welding standards data;

filtering the standardized stack-up information by using the one or more inputs defining one or more design variables;

receiving historical welding data for predicting a weldability of the stack-up;

applying predictive logic to the filtered standardized stack-up information based on the historical welding data to obtain one or more predictions on the weldability of the stack-up; and

transmitting the one or more weldability predictions of the stack-up for use in vehicle part production.

2. The computer-implemented method of claim 1 wherein generating the standardized stack-up information further comprises converting the one or more design variables to one or more physical property variables.

3. The computer-implemented method of claim 2 wherein the physical property variables are selected from the group consisting of yield strength, modulus, chemical composition, thermal composition, heat capacity, surface resistivity, bulk resistivity, surface coating material, and surface coating thickness.

4. The computer-implemented method of claim 1 wherein the applying step further comprises generating one or more welding process variables based on the historical welding data.

5. The computer-implemented method of claim 4 wherein the one or more welding process variables are selected from the group consisting of weld force, weld time, weld current, controller type, electrode type, and electrode diameter.

6. The computer-implemented method of claim 1 further comprising:

receiving one or more inputs for recommending one or more weld process schedules for the stack-up based on the one or more weldability predictions; and

recommending the one or more weld process schedules based on the one or more inputs and the welding standards data.

7. The computer-implemented method of claim 6 wherein the applying step includes generating one or more weldability prediction variables, wherein the one or more inputs for recommending one or more weld process schedules are the one or more weldability prediction variables.

8. The computer-implemented method of claim 7 wherein the one or more weldability prediction variables are selected from the group consisting of weld force, indentation, hardness, strength, fatigue and electrode life.

9. The computer-implemented method of claim 6 wherein the recommending step further comprises reporting one or more weld process schedule recommendations.

10. The computer-implemented method of claim 9 further comprising determining a weld quality index based on the one or more weldability predictions, wherein the reporting step further comprises reporting the weld quality index.

11. The computer-implemented method of claim 1 wherein the general stack up information is one or more general CAD models of stackups and wherein the standardized stackup information is one or more standardized CAD models of the stackups.

12. The computer-implemented method of claim 1 wherein the one or more design variable inputs are user inputs.

13. The computer-implemented method of claim 12 wherein the one or more design variables are selected from the group consisting of grade, gauge, coating, supplier, and number of stack-up layers.

14. A computer-implemented system for determining a weldability of a plurality of layers of materials forming a stack-up for use in vehicle part production, the computer-implemented system comprising:

at least one computer configured to;

receive general stack-up information;

receive welding standards data for welding together a plurality of materials forming a stack-up;

receive one or more inputs defining one or more design variables of the one or more stack-ups;

generate standardized stack-up information based on the general stack-up information, the one or more design variables, and the welding standards data;

filter the standardized stack-up information by using the one or more inputs defining one or more design variables;

receive historical welding data for predicting a weldability of the stack-up;

apply predictive logic to the filtered standardized stack-up information based on the historical welding data to obtain one or more predictions on the weldability of the stack-up; and

transmit the one or more weldability predictions of the stack-up for use in vehicle part production.

15. The computer-implemented system of claim 14 further comprising a historical welding database for storing the historical welding data, wherein the at least one computer is further configured to received the historical welding data from the historical welding database.

16. The computer-implemented system of claim 14 wherein the historical welding data comprises one or more learning models.

17. The computer-implemented system of claim 14 wherein the historical welding data further comprises data from one or more manufacturing plants.

18. The computer-implemented system of claim 17 wherein the data from the one or more manufacturing plants includes at least one of weld quality data, optimal process parameters, weld equipment data, or welding tip maintenance data.

19. A method comprising:

receiving general stack-up information, welding standards data, physical property variable inputs for a stack-up, and historical welding data for making a weldability prediction;

generating standardized stack-up information based on the inputs from the receiving step;

filtering the standardized stack-up information based on one or more design variables;

applying predictive logic to the filtered standardized stack-up information to obtain one or more weldability predictions; and

transmitting the weldability predictions for use in part production.

20. The method of claim 19 wherein the physical property variable inputs are generated from one or more design variables input by a user.

21. The method of claim 19 wherein the generating step further includes generating one or more welding process variables based on the inputs from the receiving step.