Manufacturing Design and Process Analysis System

• US 20110178622A1
• Filed: 03/21/2011
• Published: 07/21/2011
• Est. Priority Date: 02/04/2002
• Status: Active Grant

• Current Assignee: Steve W. Tuszynski
• Original Assignee: Steve W. Tuszynski
• Inventors: Tuszynski, Steve W.
• Granted Patent: US 8,768,500 B2
• Time in Patent Office: Days
• US Class Current: 700/103
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 2219/32058 Execute program as function of deviation from predicted state, result
• CPC Class Codes: G06F 2111/08 Probabilistic or stochastic CAD
• CPC Class Codes: G06F 2113/22 Moulding
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

Methods, apparatuses and systems that facilitate the design, production 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. This knowledge facilitates a reduction in measurement costs. 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. As discussed in more detail below, embodiments of the present invention facilitate 1.) determination of design target values, 2.) determination of design specification limits, 3.) design of process inputs, 4.) determination of process control variable settings, and/or 5.) reduction of measurement costs.

Claims

1. An apparatus facilitating design, manufacturing, and other processes comprising:

a processor;

a memory;

a software application, physically stored in a computer-readable storage medium, comprising instructions operable to cause the processor and the apparatus to;

receive into the 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;

calculate correlation coefficient values characterizing correlations between the plurality of article characteristics;

calculate predictor capability values for the plurality of article characteristics, wherein the predictor capability value for a given article characteristic is a function of the correlation coefficients corresponding to the given article characteristic;

receive a selection of a predictor characteristic from the plurality of article characteristics based on the correlations between the plurality of article characteristics; and

,

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

identify a range for the predictor characteristic over which at least one remaining article characteristic is within design specifications.

2. The apparatus of claim 1 wherein the software application further comprises instructions operable to cause the processor and the apparatus to generate a diagram of the regression model(s) for display on a display device.

3. The apparatus of claim 1 wherein the software application further comprises instructions operable to cause the processor and the apparatus to identify a range for the predictor characteristic over which a plurality of remaining article characteristics are within design specifications.

4. The apparatus of claim 1 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

display a list of the article characteristics on a graphical user interface;

and

receive, from a user via the graphical user interface, selection as the predictor characteristic from any of the plurality of article characteristics displayed in the graphical user interface.

5. The apparatus of claim 4 wherein the list is sorted based on the predictor capability values of the article characteristics.

6. The apparatus of claim 1 wherein the step of calculating the predictor capability values step comprises:

calculating the average of the absolute value of the calculated correlation coefficients for each article characteristic included in the plurality of article characteristics.

7. The apparatus of claim 1 wherein the software application further comprises instructions operable to cause the processor and the apparatus to assess, using the determined regression equation (s), the values of the predictor characteristic and article characteristic relative to the regression equation (s), for articles that may be generated by the process, the assessing step including at least one of

(1) determining whether the values of the article characteristic relative to the regression equation (s) comply with respective specification limits for all corresponding values of the predictor characteristic for articles that may be generated by the relevant process,

(2) determining whether the articles with predictor characteristic values and article characteristic values relative to the regression equation (s) can be manufactured within specification limits, according to a process setting that may be set for a relevant process, and

(3) determining a minimum value of the predictor characteristic such that the value of the article characteristic relative to the regression equation (s) complies with a corresponding specification limit for the relevant process,

(4) determining a maximum value of the predictor characteristic such that the value of the article characteristic relative to the regression equation (s) complies with a corresponding specification limit for the relevant process,

(5) determining a distance on a graph defining the regression equation (s) between a target specification value for the predictor characteristic and the article characteristic and the regression line indicating the regression equation (s).

8. A method facilitating design and manufacturing processes, the method comprising

receiving into a 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;

calculating correlation coefficient values characterizing correlations between the plurality of article characteristics;

calculating predictor capability values for the plurality of article characteristics, wherein the predictor capability value for a given article characteristic is a function of the correlation coefficients corresponding to the given article characteristic;

receiving a selection of a predictor characteristic from the plurality of article characteristics based on the correlations between the plurality of article characteristics; and

,

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

identifying a range for the predictor characteristic over which at least one remaining article characteristic is within design specifications; and

generating a representation of the range for display on the display device.

9. The method of claim 8 further comprising

generating a diagram of the regression model(s) for display on a display device.

10. The method of claim 8 further comprising

identifying a range for the predictor characteristic over which a plurality of remaining article characteristics are within design specifications;

qualifying articles resulting from the process are within design specifications based on corresponding values of the predictor characteristic relative to the identified range.

11. A method for selecting a predictor characteristic that is an article characteristic used for predicting another article characteristic value from a set of article characteristics corresponding to articles resulting from a process, the method comprising

receiving into a 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;

calculating correlation coefficient values characterizing correlations between the plurality of article characteristics;

selecting one article characteristic from the plurality of article characteristics as a predictor characteristic used for predicting another article characteristic value of an article that may be generated by the relevant process, wherein the step of selecting as a predictor characteristic comprises

calculating, for each article characteristic, the average of absolute values for a plurality of correlation coefficients calculated in relation to another article characteristic, and selecting the article characteristic corresponding to the maximum average value among the respective averages of the plurality of article characteristics as the predictor characteristic.