Dynamic control system for manufacturing processes

• US 7,660,642 B1
• Filed: 10/20/2006
• Issued: 02/09/2010
• Est. Priority Date: 11/04/2005
• Status: Active Grant

• Current Assignee: Steve W. Tuszynski
• Original Assignee: Steve W. Tuszynski
• Inventors: Tuszynski, Steve W.
• Primary Examiner(s): Jarrett; Ryan A
• Application Number:
  US11/551,331
• Time in Patent Office: 1,208 Days
• Field of Search: 700/51, 700/97, 700/29
• US Class Current: 700/97
• CPC Class Codes: G05B 19/41875 characterised by quality surveillance of production
• CPC Class Codes: G05B 2219/32187 Correlation between controlling parameters for influence on quality parameters
• CPC Class Codes: G05B 2219/32194 Quality prediction
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

Methods, apparatuses and systems that facilitate the design, production, control and/or measurement tasks associated with manufacturing and other processes. In one embodiment, the present invention provides an understanding of how the multiple characteristics of a given process output are related to each other and to process inputs. It also facilitates an understanding of the sometimes complex interrelationships between design targets, design tolerances, process inputs, process control variables, average process output and variation in the process output. In one implementation, the present invention enables or facilitates the implementation of static and dynamic control systems in connection with manufacturing or other process. For example, in one implementation, the present invention provides a dynamic control system for manufacturing processes that is responsive to the observed output of a process.

Claims

1. A method, comprising:

receiving into a computer memory a plurality of article characteristic values associated with a set of articles having a range of variation as to a plurality of article characteristics resulting from a process,

selecting a predictor characteristic from the plurality of article characteristics;

determining regression model(s) between the predictor characteristic and at least one other article characteristic of the plurality of article characteristics;

determining an operating target for the predictor characteristic based on a set of design tolerances and the regression model(s); and

using a process controller to control, during cycles of the process, at least one process setting of the process based on observed values of the predictor characteristic, relative to the operating target, resulting from the cycles of the process.

2. The method of claim 1 further comprising sampling the set of articles relative to the predictor characteristic.

3. The method of claim 1 further comprising determining the relationship between the predictor characteristic and the at least one process setting of the process.

4. The method of claim 3 further comprising computing a change to the at least one process setting of the process based on the determined relationship between the predictor dimension and the at least one process setting of the process, and the observed values of the predictor characteristic resulting from the process relative to the operating target.

5. The method of claim 1 wherein at least one attribute of the process comprises a design target;

and wherein the method further comprises

varying the design target; and

recomputing one or more of an operating target or an operating range for the predictor characteristic.

6. The method of claim 1 wherein at least one attribute of the process comprises a design tolerance;

and wherein the method further comprises

varying the design tolerance; and

recomputing one or more of an operating target or an operating range for the predictor characteristic.

7. The method of claim 1 wherein at least one attribute of the process comprises a pre-process dimension;

and wherein the method further comprises

varying the pre-process dimension; and

recomputing one or more of an operating target or an operating range for the predictor characteristic.

8. The method of claim 7 wherein the varying step is time dependent.

9. The method of claim 7 wherein the varying step is cycle dependent.

10. The method of claim 7 wherein the varying step is based on a model expressing a value of the pre-process dimension as function of at least one variable.

11. The method of claim 10 wherein the at least one variable is time.

12. The method of claim 10 wherein the at least one variable is the number of cycles.

13. A computer program product comprising a computer-readable medium storing computer executable instructions, the computer executable instructions, when executed, operable to cause one or more processors to:

select a predictor characteristic from a plurality of article characteristics based on a plurality of article characteristic values associated with a set of articles resulting from a process and having a range of variation as to the plurality of article characteristics;

determine regression model(s) between the predictor characteristic and at least one other article characteristic of the plurality of article characteristics;

determine an operating target for the predictor characteristic based on a set of design tolerances and the regression model(s); and

compute at least one attribute operative to control, during cycles of the process, one or more process control settings of the process based on values of the predictor characteristic, relative to the operating target, observed during the cycles of the process.

14. An apparatus comprising

a memory;

one or more processors;

logic encoded in one or more tangible media for execution and when executed operable to cause the one or more processors to;

select a predictor characteristic from a plurality of article characteristics based on a plurality of article characteristic values associated with a set of articles resulting from a process and having a range of variation as to the plurality of article characteristics;

determine regression model(s) between the predictor characteristic and at least one other article characteristic of the plurality of article characteristics;

determine an operating target for the predictor characteristic based on a set of design tolerances and the regression model(s); and

compute at least one attribute operative to control, during cycles of the process, one or more process control settings of the process based on values of the predictor characteristic, relative to the operating target, observed during the cycles of the process.