Manufacturing design and process analysis system

• US 20030176938A1
• Filed: 02/04/2002
• Published: 09/18/2003
• 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 7,072,808 B2
• Time in Patent Office: Days
• US Class Current: 700/97
• 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. A method facilitating design and manufacturing processes, the method comprising

receiving a plurality of article characteristic values associated with a set of articles having a range of variation as to a plurality of article characteristics;

selecting a predictor characteristic from 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.

2. The method of claim 1 further comprising

receiving a target value for the predictor characteristic and a target value for at least one remaining article characteristic;

determining the intersection of the target value for the predictor characteristic and the target value of a first remaining article characteristic relative to the regression model between the predictor characteristic and the first remaining article characteristic.

3. The method of claim 1 further comprising

determining the respective upper and lower prediction intervals associated with the regression model(s) between the predictor characteristic and at least one of the remaining article characteristics.

4. The method of claim 2 further comprising

determining the respective upper and lower prediction intervals associated with the regression model(s) between the predictor characteristic and at least one of the remaining article characteristics.

5. The method of claim of 4 further comprising

receiving lower and upper specification limits for the predictor characteristic and at least one of the remaining article characteristics;

locating the lower and upper specification limits associated with said at least one remaining article characteristic;

locating the upper and lower specification limits associated with the predictor characteristic.

6. The method of claim 1 further comprising

receiving lower and upper specification limits for at least one of the remaining article characteristics;

locating the lower and upper specification limits associated with at least one remaining article characteristic relative to the regression model between the predictor characteristic and said at least one remaining article characteristic.

7. The method of claim 6 further comprising

determining the value of the predictor characteristic at which the corresponding regression model intersects the upper specification limit for at least one remaining article characteristic.

8. The method of claim 6 or 7 further comprising

determining the value of the predictor characteristic at which the corresponding regression model intersects the lower specification limit for at least one remaining article characteristic.

9. The method of claim 3 further comprising

receiving lower and upper specification limits for at least one of the remaining article characteristics;

locating the specification limits associated with said at least one remaining article characteristic relative to the regression model between the predictor characteristic and said at least one remaining article characteristic.

10. The method of claim 9 further comprising

determining the value of the predictor characteristic at which the upper prediction interval associated with the regression model between the predictor characteristic and said at least one remaining article characteristic intersects the upper specification limit for said at least one remaining article characteristic.

11. The method of claim 9 or further comprising

determining the value of the predictor characteristic at which the lower prediction interval associated with the regression model between the predictor characteristic and said at least one remaining article characteristic intersects the lower specification limit for said at least one remaining article characteristic.

12. The method of claim 6 further comprising

receiving the lower and upper specification limits for the predictor characteristic;

and

locating the upper and lower specification limits associated with the predictor characteristic.

13. The method of claim 8 further comprising

receiving the lower and upper specification limits for the predictor characteristic;

and

locating the upper and lower specification limits associated with the predictor characteristic.

14. The method of claim 3 further comprising

receiving lower and upper specification limits for said at least one of the remaining article characteristics;

locating the lower and upper specification limits associated with said at least one of the remaining article characteristics;

receiving lower and upper specification limits for the predictor characteristic;

locating the upper specification limit associated with the predictor characteristic; and

determining a maximum article characteristic value for the predictor characteristic by selecting the lesser of (1) the upper specification limit for the predictor characteristic and (2) the value of the predictor characteristic at which the upper prediction interval intersects the upper specification limit for said at least one remaining article characteristic.

15. The method of claim 14 further comprising

repeating the determining a maximum article characteristic value step for a desired number of remaining article characteristics in the plurality of article characteristics;

and

determining the most constraining maximum article characteristic value for the predictor characteristic by selecting the lowest maximum article characteristic value.

16. The method of claim 14 further comprising

receiving lower and upper specification limits for at least one of the remaining article characteristics;

locating the lower specification limit associated with the predictor characteristic; and

determining a minimum article characteristic value for the predictor characteristic by selecting the greater of (1) the lower specification limit for the predictor characteristic and (2) the value of the predictor characteristic at which the lower prediction interval intersects the lower specification limit for said at least one remaining article characteristic.

17. The method of claim 16 further comprising

determining an allowable range for the predictor characteristic subtracting the minimum article characteristic value from the maximum characteristic value.

18. The method of claim 16 further comprising

repeating the determining a minimum article characteristic value step for a desired number remaining article characteristics in the plurality of article characteristics;

and

determining the most constraining minimum article characteristic value for the predictor characteristic by selecting the greatest minimum article characteristic value.

19. The method of claim 18 further comprising

determining the maximum allowable range for the predictor characteristic by subtracting the most constraining minimum article characteristic value from the most constraining maximum characteristic value.

20. The method of claim 19 further comprising

determining the target manufacturing value for the predictor characteristic by selecting a value between the most constraining minimum and maximum article characteristic values for the predictor characteristic.

21. The method of claim 19 further comprising

determining the target manufacturing value for the predictor characteristic by selecting the midpoint value between the most constraining minimum and maximum values for the predictor characteristic.

22. The method of claim 21 further comprising

receiving a target value for the predictor characteristic and a target value for at least one remaining article characteristic;

determining the intersection of the target value for the predictor characteristic and the target value of a first remaining article characteristic relative to the regression model between the predictor characteristic and the first remaining article characteristic.

23. The method of claim 1 wherein the selecting step comprises

selecting the predictor characteristic based at least in part on an assessment of the capability of each article characteristic to be predictive of all or a subset of the article characteristics in the plurality of article characteristics.

24. The method of claim 23 wherein the selecting step comprises

calculating the correlation coefficients between all or a subset of the article characteristics;

determining, based on the calculated correlation coefficients, a value indicating the predictive capability of a first article characteristic relative to all other article characteristics;

repeating the determining step for said all or a subset of the article characteristics, and

selecting a predictor characteristic based at least in part on the values indicating the predictive capabilities of the article characteristics.

25. The method of claim 24 wherein the predictor characteristic is selected as the article characteristic associated with the value indicating the highest predictive capability.

26. The method of claim 24 further comprising

ranking the article characteristics based on the values computed in the determining step.

27. The method of claim 24 wherein the determining step comprises

calculating the average correlation coefficient for each article characteristic.

28. The method of claim 24 wherein the determining step comprises

calculating the average of the absolute values of the correlation coefficients for each article characteristic.

29. The method of claim 23 wherein the predictor characteristic is selected based on a graphical determination of the article characteristic having the greatest predictive capabilities.

30. The method of claim 23 wherein selection of the predictor characteristic is further based on factors associated with assessing each article characteristic.

33. The method of claim 28 further comprising

ranking the article characteristics based on the values computed in the determining step;

and

wherein selection of the predictor characteristic is further based on economic or technical factors associated with assessing each article characteristic.

31. The method of claim wherein the factors comprise the economic factors associated with assessing each article characteristic.

32. The method of claim wherein the factors comprise the technical factors associated with assessing each article characteristic.

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

receiving a plurality of article characteristic values associated with a set of articles having a range of variation as to a plurality of article characteristics;

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

receiving a target value for the first article characteristic and a target value for said at least one of the remaining article characteristic; and

determining the intersection between the target value for the first article characteristic and a target value for said at least one remaining article characteristic.

35. The method of claim 34 wherein regression models are determined for all possible combinations of article characteristics in the plurality of article characteristics.

36. The method of claim 34 wherein regression models are determined for a subset of all possible combinations of article characteristics in the plurality of article characteristics.

37. The method of claim 34, 35 or 36 further comprising

displaying the regression model(s) on a user interface display.

38. The method of claim 37 wherein the regression model(s) are graphically displayed in scatter diagrams on the user interface display.

39. The method of claim 34 further comprising

receiving the lower and upper specification limits for said at least one remaining article characteristics;

locating the specification limits associated with said at least one remaining article characteristic.

40. The method of claim 39 further comprising

receiving the lower and upper specification limits for the first article characteristic;

locating the lower and upper specification limits for the first article characteristic.

41. The method of claim 39 further comprising

(a) determining the value of the first article characteristic at which the regression model intersects the upper specification limit for said at least one remaining article characteristic.

42. The method of claim 39 or 41 further comprising

determining the value of the first article characteristic at which the regression model intersects the lower specification limit for said at least one remaining article characteristic.

43. The method of claim 41 further comprising

repeating the determining step (a) for a desired number of remaining article characteristics;

and

determining the most constraining maximum value for the first article characteristic by selecting the lowest value of the first article characteristic associated with the determining step (a).

44. The method of claim 43 further comprising

(b) determining the value of the first article characteristic at which the regression model intersects the lower specification limit for said at least one remaining article characteristic;

repeating the determining step for a desired number of remaining article characteristics; and

determining the most constraining minimum value for the first article characteristic by selecting the greatest value of the first article characteristic associated with the determining step (b).

45. The method of claim 44 further comprising

determining the target manufacturing value for the first characteristic by selecting the midpoint between the most constraining minimum and maximum values for the first article characteristic.

47. The method of claim 44 further comprising

determining the target manufacturing value for the first characteristic by selecting a value between the most constraining minimum and maximum values for the first article characteristic.

48. The method of claim 41 further comprising

receiving the lower and upper specification limits for the first article characteristic;

and

locating the lower and upper specification limits associated with the first article characteristic;

repeating the determining step (a) for a desired number of remaining article characteristics; and

determining the most constraining maximum value for the first article characteristic by selecting the lower of (1) the upper specification limit for the first article characteristic and (2) the lowest value computed in the determining step (a).

49. The method of claim 47 further comprising

(b) determining the value of the first article characteristic at which the regression model intersects the lower specification limit for said at least one remaining article characteristic;

repeating the determining step (b) for a desired number of remaining article characteristics; and

determining the most constraining minimum value for the first article characteristic by selecting the greater of (1) the lower specification limit for the first article characteristic and (2) the greatest value of the first article characteristic computed in the determining step (b).

46. The method of 44 further comprising

determining the maximum allowable range for the first article characteristic by subtracting the most constraining minimum value for the first article characteristic from the most constraining maximum value for the first article characteristic.

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

receiving a plurality of article characteristic values associated with a set of articles having a range of variation as to a plurality of article characteristics;

determining a first regression model between a first article characteristic and a second article characteristic;

determining at least a second regression model between the first article characteristic and at least one of the remaining article characteristics; and

,

facilitating a comparison between the regression models.

51. The method of claim 50 wherein regression models are determined for all possible combinations of article characteristics in the plurality of article characteristics.

52. The method of claim 50 wherein regression models are determined for a subset of all possible combinations of article characteristics in the plurality of article characteristics.

53. The method of claim 50, 51, or 52 further comprising

displaying the regression model(s) on a user interface display.

54. The method of claim 53 wherein the regression models are graphically displayed in scatter diagrams on the user interface display.

55. The method of claim 50 further comprising

receiving a target value as to at least two article characteristics;

as to a first article characteristic and a second article characteristic, locating the intersection of the target values of the first and second article characteristics relative to the regression model associated with the first and second article characteristics.

56. The method of claim 55 further comprising

As to the first article characteristic and a third article characteristic, locating the intersection of the target values of the first and third article characteristics relative to the regression model associated with the first and third article characteristics.

57. The method of claim 50 further comprising

receiving the lower and upper specification limits for the second article characteristic and a third article characteristic;

locating the specification limits associated with the second article characteristic relative to the regression model between the first article characteristic and the second article characteristic;

locating the specification limits associated with the third article characteristic relative to the regression model between the third article characteristic and the first article characteristic.

58. The method of claim 56 further comprising

receiving the lower and upper specification limits for the first article characteristic;

locating the specification limits for the first article characteristic relative to the regression model between the first article characteristic and the second article characteristic; and

locating the specification limits for the first article characteristic relative to the regression model between the first article characteristic and the third article characteristic.

59. A method facilitating design and manufacturing processes associated with the production of an article, the article having a plurality of article characteristics, at least two of the article characteristics having a target value and upper and lower specification limits, the method comprising

generating a set of articles having a range of variation as to a plurality of article characteristics;

assessing the set of articles as to all or a subset of the plurality of article characteristics;

selecting a predictor characteristic from 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.

60. The method of claim 59 further comprising

determining the intersection of the target value for the predictor characteristic and the target value of at least one remaining article characteristic relative to the regression model between the predictor characteristic and said at least one remaining article characteristic.

61. The method of claim 59 further comprising

determining the respective upper and lower prediction intervals associated with the regression model between the predictor characteristic and said at least one of the remaining article characteristics.

62. The method of claim 60 further comprising

determining the respective upper and lower prediction intervals associated with the regression model(s) between the predictor characteristic and said at least one of the remaining article characteristics.

63. The method of claim of 62 further comprising

locating the lower and upper specification limits associated with said at least one remaining article characteristic;

locating the upper and lower specification limits associated with the predictor characteristic.

64. The method of claim 59 further comprising

locating the specification limits associated with said at least one remaining article characteristic.

65. The method of claim 64 further comprising

determining the value of the predictor characteristic at which the regression model intersects the upper specification limit for said at least one remaining article characteristic.

66. The method of claim 64 or 65 further comprising

determining the value of the predictor characteristic at which the regression model intersects the lower specification limit for said at least one remaining article characteristic.

67. The method of claim 61 further comprising

locating the specification limits associated with said at least one remaining article characteristic.

68. The method of claim 67 further comprising

determining the value of the predictor characteristic at which the upper prediction interval associated with the regression model between the predictor characteristic and said at least one remaining article characteristic intersects the upper specification limit for said at least one remaining article characteristic.

69. The method of claim 67 or 68 further comprising

determining the value of the predictor characteristic at which the lower prediction interval associated with the regression model between the predictor characteristic and said at least one remaining article characteristic intersects the lower specification limit for said at least one remaining article characteristic.

70. The method of claim 64 further comprising

locating the upper and lower specification limits associated with the predictor characteristic.

71. The method of claim 66 further comprising

locating the upper and lower specification limits associated with the predictor characteristic.

72. The method of claim 61 further comprising

locating the lower and upper specification limits associated with said at least one remaining article characteristic.

locating the upper specification limit associated with the predictor characteristic;

and

determining a maximum article characteristic value for the predictor characteristic by selecting the lesser of (1) the upper specification limit for the predictor characteristic and (2) the value of the predictor characteristic at which the upper prediction interval intersects the upper specification limit for said at least one remaining article characteristic.

73. The method of claim 72 further comprising

repeating the determining a maximum article characteristic value step for a desired number of remaining article characteristics in the plurality of article characteristics;

and

determining the most constraining maximum article characteristic value for the predictor characteristic by selecting the lowest maximum article characteristic value.

74. The method of claim 72 further comprising

locating the lower specification limit associated with the predictor characteristic;

and

determining a minimum article characteristic value for the predictor characteristic by selecting the greater of (1) the lower specification limit for the predictor characteristic and (2) the value of the predictor characteristic at which the lower prediction interval intersects the lower specification limit for said at least one remaining article characteristic.

75. The method of claim 74 further comprising

determining an allowable range for the predictor characteristic by subtracting the minimum article characteristic value from the maximum characteristic value.

76. The method of claim 74 further comprising

repeating the determining a minimum article characteristic value step for a desired number of remaining article characteristics;

and

determining the most constraining minimum article characteristic value for the predictor characteristic by selecting the greatest minimum article characteristic value.

77. The method of claim 76 further comprising

determining the maximum allowable range for the predictor characteristic by subtracting the most constraining minimum article characteristic value from the most constraining maximum characteristic value.

78. The method of claim 76 further comprising

determining the target manufacturing value for the predictor characteristic by selecting a value between the most constraining minimum and maximum values for the predictor characteristic.

79. The method of claim 76 further comprising

determining the target manufacturing value for the predictor characteristic by selecting the midpoint value between the most constraining minimum and maximum values for the predictor characteristic.

80. The method of claim 79 determining the intersection of the target value for the predictor characteristic and the target value of at least one remaining article characteristic relative to the regression model between the predictor characteristic and said at least one remaining article characteristic.

81. The method of claim 59 wherein the selecting step comprises

selecting the predictor characteristic based at least in part on an assessment of the capabilities of each article characteristic to be predictive of the other article characteristics in the plurality of article characteristics.

82. The method of claim 81 wherein the selecting step comprises

calculating the correlation coefficients between all or a subset of the article characteristics;

determining, based on the calculated correlation coefficients, a value indicating the predictive capability of a first article characteristic relative to all other article characteristics;

repeating the determining step for all article characteristics; and

selecting a predictor characteristic based at least in part on the values indicating the predictive capabilities of the article characteristics.

83. The method of claim 82 wherein the predictor characteristic is selected as the article characteristic associated with the value indicating the highest predictive capability.

84. The method of claim 82 further comprising

ranking the article characteristics based on the values computed in the determining step.

85. The method of claim 82 wherein the determining step comprises

calculating the average correlation coefficient for each article characteristic.

86. The method of claim 82 wherein the determining step comprises

calculating the average of the absolute values of the correlation coefficients for each article characteristic.

87. The method of claim 81 wherein the predictor characteristic is selected based on a graphical determination of the article characteristic having the greatest predictive capabilities.

88. The method of claim 81 wherein the selection of the predictor characteristic is further based on factors associated with assessing each article characteristic.

89. The method of claim 88 wherein the factors comprise the economic factors associated with assessing each article characteristic.

90. The method of claim 88 wherein the factors comprise the technical factors associated with assessing each article characteristic.

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

generating a set of articles having a range of variation as to a plurality of article characteristics;

assessing the degree of correlation between the article characteristics; and

,

selecting a predictor characteristic from the plurality of article characteristics based on the assessing step.

92. The method of claim 91 further comprising

determining a maximum allowable range for the predictor characteristic;

and,

subsequent to the determining step, verifying that subsequently generated articles comply with at least one design specification associated with said articles based on assessment of the predictor characteristic.