Manufacturing design and process analysis system

• US 7,187,992 B2
• Filed: 01/07/2004
• Issued: 03/06/2007
• Est. Priority Date: 02/04/2002
• Status: Expired due to Fees

• Current Assignee: Steve W. Tuszynski
• Original Assignee: Steve W. Tuszynski
• Inventors: Tuszynski, Steve W.
• Primary Examiner(s): Paladini; Albert W.
• Application Number:
  US10/752,843
• Publication Number:
  US 20040167648A1
• Time in Patent Office: 1,154 Days
• Field of Search: 703/2, 705/7, 700/33, 700/97
• 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 relates to decision-making and logic structures, implemented in a computer software application, facilitating all phases of the design, development, tooling, pre-production, qualification, certification, and production process of any part or other article that is produced to specification. In one embodiment, the present invention provides knowledge of how the multiple characteristics of a given process output are related to each other, to specification limits and to pre-process inputs. This knowledge facilitates a reduction in measurement, analysis and reporting costs both prior to and during production. It also determines the changes needed to pre-process inputs in order to achieve production at design targets. It provides a prioritized order for relaxing design tolerances. It assesses the feasibility of producing parts that meet specification limits. It assesses the trade-off between performance and producibility and provides design targets that improve-producibility. It provides a determination of when process variability needs reduction. It facilitates material comparison and selection. It provides process engineers and operators with improved operating guidelines.

Claims

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

a processor;

a memory;

a software application, physically stored in the memory, comprising instructions operable to cause the processor and the apparatus to;

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

select a predictor characteristic from the plurality of article characteristics;

determine the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics, wherein the regression model includes lower and upper prediction boundaries

receive lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;

locate, relative to the regression model between the predictor characteristic and the first remaining article characteristic, the compliance area bounded by the upper and lower specification limits associated with the first remaining article characteristic and the predictor characteristic;

locate the bounded regression area for the first remaining characteristic defined by the upper and lower prediction boundaries of the regression model and the upper and lower specification limits for the predictor characteristic; and

identify the relationship between the bounded regression area and the compliance area.

2. The apparatus of claim 1 wherein the identified relationship characterizes the structure of the geometric relationship between the bounded regression area and the compliance area.

3. The apparatus of claim 1 wherein the identified relationship characterizes the relationship between the perimeter elements that define the bounded regression area and the perimeter elements that define the compliance area.

4. The apparatus of claim 1 wherein the identified relationship is one from the group consisting of a defect potential relationship, a robust relationship and a constraining relationship.

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

determine whether the bounded regression area lies completely within the compliance area.

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

if the bounded regression area lies completely within the compliance area, set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

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

determine whether the bounded regression area extends above, below, or both above and below the compliance area over the specification limit range of the predictor characteristic;

and

if so, report a defect condition as to the first remaining article characteristic.

8. The apparatus of claim 6 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether the bounded regression area extends above, below, or both above and below the compliance area over the specification limit range of the predictor characteristic;

and

if so, report a defect condition as to the first remaining article characteristic.

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

determine whether any horizontal segment of the bounded regression area is contained completely within the compliance area and whether a second horizontal segment extends partially or completely outside of the compliance area;

and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

10. The apparatus of claim 9 to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the software application further comprises instructions operable to cause the processor and the apparatus to

determine the slope and intercept of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

11. The apparatus of claim 8 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether any horizontal segment of the bounded regression area is contained completely within the compliance area and whether a second horizontal segment extends partially or completely outside of the compliance area;

and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

12. The apparatus of claim 11 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

store the resulting minimum and maximum predictor characteristic values in association with the corresponding remaining article characteristic in a data structure.

13. The apparatus of claim 12 wherein the data structure is an array.

14. The apparatus of claim 12 wherein, to report a defect condition, the software further comprises instructions operable to store a defect identifier in association with the corresponding remaining article characteristic.

15. The apparatus of claim 12 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

display the resulting minimum and maximum predictor characteristic values and/or defect identifiers in association with the corresponding remaining article characteristic.

16. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether all vertical cross sections of the bounded regression area lie within the compliance area.

17. The apparatus of claim 16 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

if all vertical cross sections of the bounded regression area lie within the compliance area, set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

18. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether all vertical cross-sections of the bounded regression area are fully or partially outside of the compliance area;

and

if so, report a defect condition as to the first remaining article characteristic.

19. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether at least one vertical cross section of the bounded regression area is completely within the compliance region and whether at least one vertical cross section is partially or completely outside the compliance area;

and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

20. The apparatus of claim 19 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the software application further comprises instructions operable to cause the processor and the apparatus to

determine the slope of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

21. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether the lower and upper boundaries of the bounded regression area are completely within the compliance region.

22. The apparatus of claim 21 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

if the lower and upper boundaries of the bounded regression area are completely within the compliance region, set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

23. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether either of the lower and upper boundaries of the bounded regression area fail to intersect the compliance area;

and

if so, report a defect condition as to the first remaining article characteristic.

24. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

determine whether the upper boundary of the bounded regression area intersects the upper boundary of the compliance area and the lower boundary of the bounded regression area intersects the compliance area;

and, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic;

else, determine whether the lower boundary of the bounded regression area intersects the lower boundary of the compliance area and the upper boundary of the bounded regression area intersects the compliance area; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

25. The apparatus of claim 24 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the software application further comprises instructions operable to cause the processor and the apparatus to

determine the slope of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

26. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

compute the upper and lower prediction boundary values for the first remaining article characteristic at the upper and lower specification limits of the predictor characteristic;

determine whether the upper prediction boundary values are both less than the upper specification limit for the first remaining article characteristic, and whether the lower prediction boundary values are both greater than the lower specification limit for the first remaining article characteristic.

27. The apparatus of claim 26 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

if the upper prediction boundary values are both less than the upper specification limit for the first remaining article characteristic, and the lower prediction boundary values computed by the apparatus are both greater than the lower specification limit for the first remaining article characteristic, then

set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

28. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

compute the upper and lower prediction boundary values for the first remaining article characteristic at the upper and lower specification limits of the predictor characteristic;

if the upper prediction boundary values are both greater than the upper specification limit for the first remaining article characteristic, then report a defect condition as to the first remaining article characteristic; and

if the lower prediction boundary values are both less than the lower specification limit for the first remaining article characteristic, then report a defect condition as to the first remaining article characteristic.

29. The apparatus of claim 1 wherein to identify the relationship between the bounded regression area and the compliance area, the software application further comprises instructions operable to cause the processor and the apparatus to

compute the upper and lower prediction boundary values for the first remaining article characteristic at the upper and lower specification limits of the predictor characteristic;

determine whether one of the upper prediction boundary values is less than, and the other of the upper prediction boundary values is greater than, the upper specification limit of the first remaining article characteristic, and both of the lower prediction boundary values are greater than the upper specification limit for the first remaining article characteristic; and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic;

else, determine whether one of the lower prediction boundary values is less than, and the other of the lower prediction boundary values is greater than, the lower specification limit for the first remaining article characteristic, and whether the upper prediction boundary values, are both less than the upper specification limit of the first remaining article characteristic; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic;

else, determine whether one of the upper prediction boundary values is less than, and the other of the upper prediction boundary values is greater than, the upper specification limit of the first remaining article characteristic, and whether one of the lower prediction boundary values is less than, and the other of the lower prediction boundary values is greater than, the lower specification limit for the first remaining article characteristic; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

30. The apparatus of claim 29 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the software application further comprises instructions operable to cause the processor and the apparatus to

determine the slope of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

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

repeat the determine the regression model, receive the specification limits, locate the compliance area, locate the bounded regression area, and identify the relationship operations for all desired remaining article characteristics.

32. The apparatus of claim 31 wherein the software application further comprises instructions operable to cause the processor and the apparatus to display the identified relationships.

33. The apparatus of claim 31 wherein the software application further comprises instructions operable to cause the processor and the apparatus to store the identified relationships in a data structure.

34. An apparatus facilitating a determination of the magnitude and direction by which a pre-process characteristic would have to be adjusted to achieve a given design target comprising:

a processor;

a memory;

a software application, physically stored in the memory, comprising instructions operable to cause the processor and the apparatus to;

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

select a predictor characteristic from the plurality of article characteristics;

determine the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics,

receive the target values for the predictor characteristic and the first remaining article characteristic;

compute, based on the regression model, the value of the first remaining article characteristic at the target value of the predictor characteristic;

determine the magnitude and direction of the offset for the first remaining article characteristic by computing the difference between the computed value of the first remaining article characteristic and the target value of the first remaining article characteristic;

store the magnitude and direction of the offset in a data structure in association with an identifier for the first remaining article characteristic; and

repeat the computing, determining and storing operations for all desired remaining characteristics.

35. The apparatus of claim 34 wherein the software application further comprises instructions operable to cause the processor and the apparatus to display the resulting magnitudes and directions of the offsets in association with the corresponding remaining article characteristics.

36. An apparatus facilitating analysis of the achievable gains in operating range associated with relaxing design tolerances corresponding to at least one article characteristic, comprising

a processor;

a memory;

a software application, physically stored in the memory, comprising instructions operable to cause the processor and the apparatus to;

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

select a predictor characteristic from the plurality of article characteristics;

determine the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics, wherein the regression model includes lower and upper prediction boundaries;

receive lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;

compute, based on the regression model, the minimum and maximum predictor characteristic values at which the first remaining article characteristic remains within the lower and upper specification limits of the first remaining article characteristic;

repeat the determining, receiving, and computing operations for all desired remaining article characteristics;

create a most constraining minimum predictor characteristic list by ranking the remaining article characteristics by the respective minimum predictor characteristic values associated therewith; and

starting with the remaining article characteristic associated with the greatest minimum predictor characteristic value;

compute the individual gain in operating range achieved by relaxing the applicable specification limit of the remaining article characteristic to the value corresponding to the minimum predictor characteristic value associated with the next remaining article characteristic in the ranked list;

compute the cumulative gain associated with relaxing the applicable specification limit of the corresponding article characteristic; and

repeat the first and second computing operations for all desired remaining article characteristics.

37. The apparatus of claim 36 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

create a most constraining maximum predictor characteristic list by ranking the remaining article characteristics by the respective maximum predictor characteristic values associated therewith;

and

starting with the remaining article characteristic associated with the lowest maximum predictor characteristic value;

compute the individual gain in operating range achieved by relaxing the applicable specification limit of the remaining article characteristic to the value corresponding to the maximum predictor characteristic value associated with the next remaining article characteristic in the ranked list,

compute the cumulative gain associated with relaxing the applicable specification limit of the corresponding article characteristic; and

,

repeat the first and second computing operations for all desired remaining article characteristics.

38. The apparatus of claim 37 wherein the software application further comprises instructions operable to cause the processor and the apparatus to

receive a selection of at least one remaining article characteristic from either or both of the most constraining minimum or maximum predictor characteristic list;

if the selection includes a remaining article characteristic from the most constraining minimum predictor characteristic list, then;

set the minimum predictor characteristic value to the minimum predictor characteristic value corresponding to the next article characteristic in the most constraining minimum predictor characteristic list, and

for all article characteristics in the most constraining minimum predictor characteristic list up to the selected article characteristic, compute the new lower or upper specification limit for the article characteristic; and

if the selection includes a remaining article characteristic from the most constraining maximum predictor characteristic list, then;

set the maximum predictor characteristic value to the maximum predictor characteristic value corresponding to the next article characteristic in the most constraining maximum predictor characteristic list, and

for all article characteristics in the most constraining maximum predictor characteristic list up to the selected article characteristic, determine the new lower or upper specification limit for the article characteristic.

39. A computer program product, physically stored on a machine-readable medium, for facilitating design, manufacturing, and other processes, comprising instructions operable to cause a programmable processor to:

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

select a predictor characteristic from the plurality of article characteristics;

determine the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics, wherein the regression model includes lower and upper prediction boundaries

receive lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;

locate, relative to the regression model between the predictor characteristic and the first remaining article characteristic, the compliance area bounded by the upper and lower specification limits associated with the first remaining article characteristic and the predictor characteristic;

locate the bounded regression area for the first remaining characteristic defined by the upper and lower prediction boundaries of the regression model and the upper and lower specification limits for the predictor characteristic; and

identify the relationship between the bounded regression area and the compliance area.

40. The computer program product of claim 39 wherein the identified relationship characterizes the structure of the geometric relationship between the bounded regression area and the compliance area.

41. The computer program product of claim 39 wherein the identified relationship characterizes the relationship between the perimeter elements that define the bounded regression area and the perimeter elements that define the compliance area.

42. The computer program product of claim 39 wherein the identified relationship is one from the group consisting of a defect potential relationship, a robust relationship and a constraining relationship.

43. The computer program product of claim 39 wherein the instructions are further operable to cause the programmable processor to:

determine whether the bounded regression area lies completely within the compliance area.

44. The computer program product of claim 39 wherein the instructions are further operable to cause the programmable processor to:

if the bounded regression area lies completely within the compliance area, set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

45. The computer program product of claim 39 wherein the instructions are further operable to cause the programmable processor to:

determine whether the bounded regression area extends above, below, or both above and below the compliance area over the specification limit range of the predictor characteristic; and

if so, report a defect condition as to the first remaining article characteristic.

46. The computer program product of claim 39 wherein the instructions are further operable to cause the programmable processor to:

determine whether the bounded regression area extends above, below, or both above and below the compliance area over the specification limit range of the predictor characteristic; and

if so, report a defect condition as to the first remaining article characteristic.

47. The computer program product of claim 39 wherein the instructions are further operable to cause the programmable processor to:

determine whether any horizontal segment of the bounded regression area is contained completely within the compliance area and whether a second horizontal segment extends partially or completely outside of the compliance area; and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

48. The computer program product of claim 47 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the instructions operable to cause the programmable processor to

determine the slope and intercept of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

49. The computer program product of claim 46 wherein the instructions are further operable to cause the programmable processor to:

determine whether any horizontal segment of the bounded regression area is contained completely within the compliance area and whether a second horizontal segment extends partially or completely outside of the compliance area; and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

50. The computer program product of claim 49 wherein the instructions are further operable to cause the programmable processor to:

store the resulting minimum and maximum predictor characteristic values in association with the corresponding remaining article characteristic in a data structure.

51. The computer program product of claim 50 wherein the data structure is an array.

52. The computer program product of claim 49 wherein, to report a defect condition, the instructions are further operable to cause the programmable processor to store a defect identifier in association with the corresponding remaining article characteristic.

53. The computer program product of claim 50 wherein the instructions are further operable to cause the programmable processor to:

display the resulting minimum and maximum predictor characteristic values and/or defect identifiers in association with the corresponding remaining article characteristic.

54. The computer program product of claim 39 wherein, to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

determine whether all vertical cross sections of the bounded regression area lie within the compliance area.

55. The computer program product of claim 54 wherein the instructions are further operable to cause the programmable processor to:

if all vertical cross sections of the bounded regression area lie within the compliance area, set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

56. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

determine whether all vertical cross-sections of the bounded regression area are fully or partially outside of the compliance area; and

if so, report a defect condition as to the first remaining article characteristic.

57. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

determine whether at least one vertical cross section of the bounded regression area is completely within the compliance region and whether at least one vertical cross section is partially or completely outside the compliance area; and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

58. The computer program product of claim 57 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the instructions are further operable to cause the programmable processor to:

determine the slope of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

59. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

determine whether the lower and upper boundaries of the bounded regression area are completely within the compliance region.

60. The computer program product of claim 57 wherein the instructions are further operable to cause the programmable processor to:

if the lower and upper boundaries of the bounded regression area are completely within the compliance region, set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

61. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

determine whether either of the lower and upper boundaries of the bounded regression area fail to intersect the compliance area; and

if so, report a defect condition as to the first remaining article characteristic.

62. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

determine whether the upper boundary of the bounded regression area intersects the upper boundary of the compliance area and the lower boundary of the bounded regression area intersects the compliance area; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic;

else, determine whether the lower boundary of the bounded regression area intersects the lower boundary of the compliance area and the upper boundary of the bounded regression area intersects the compliance area; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

63. The computer program product of claim 62 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the instructions are further operable to cause the programmable processor to:

determine the slope of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

64. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

compute the upper and lower prediction boundary values for the first remaining article characteristic at the upper and lower specification limits of the predictor characteristic;

determine whether the upper prediction boundary values are both less than the upper specification limit for the first remaining article characteristic, and whether the lower prediction boundary values are both greater than the lower specification limit for the first remaining article characteristic.

65. The computer program product of claim 64 wherein the instructions are further operable to cause the programmable processor to:

if the upper prediction boundary values are both less than the upper specification limit for the first remaining article characteristic, and the lower prediction boundary values computed by the apparatus are both greater than the lower specification limit for the first remaining article characteristic, then

set the minimum and maximum predictor characteristic values associated with the first remaining article characteristic to the lower and upper specification limits, respectively, of the predictor characteristic.

66. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

compute the upper and lower prediction boundary values for the first remaining article characteristic at the upper and lower specification limits of the predictor characteristic;

if the upper prediction boundary values are both greater than the upper specification limit for the first remaining article characteristic, then report a defect condition as to the first remaining article characteristic; and

if the lower prediction boundary values are both less than the lower specification limit for the first remaining article characteristic, then report a defect condition as to the first remaining article characteristic.

67. The computer program product of claim 39 wherein to identify the relationship between the bounded regression area and the compliance area, the instructions are further operable to cause the programmable processor to:

compute the upper and lower prediction boundary values for the first remaining article characteristic at the upper and lower specification limits of the predictor characteristic;

determine whether one of the upper prediction boundary values is less than, and the other of the upper prediction boundary values is greater than, the upper specification limit of the first remaining article characteristic, and both of the lower prediction boundary values are greater than the upper specification limit for the first remaining article characteristic; and

if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic;

else, determine whether one of the lower prediction boundary values is less than, and the other of the lower prediction boundary values is greater than, the lower specification limit for the first remaining article characteristic, and whether the upper prediction boundary values, are both less than the upper specification limit of the first remaining article characteristic; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic;

else, determine whether one of the upper prediction boundary values is less than, and the other of the upper prediction boundary values is greater than, the upper specification limit of the first remaining article characteristic, and whether one of the lower prediction boundary values is less than, and the other of the lower prediction boundary values is greater than, the lower specification limit for the first remaining article characteristic; and

, if so, compute the minimum and maximum predictor characteristic values for the first remaining article characteristic.

68. The computer program product of claim 67 wherein to compute the minimum and maximum predictor characteristic values for the first remaining article characteristic, the instructions are further operable to cause the programmable processor to:

determine the slope of the regression model between the predictor characteristic and the first remaining article characteristic;

determine the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic;

determine the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

if the slope of the regression model is positive, then;

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic;

otherwise, if the slope of the regression model is negative, then

set the maximum predictor characteristic value associated with the first remaining article characteristic to the lesser of the upper specification limit of the predictor characteristic or the value of the predictor characteristic at which the lower prediction boundary corresponding to the regression model intersects the lower specification limit for the first remaining article characteristic; and

set the minimum predictor characteristic value associated with the first remaining article characteristic to the greater of the lower specification limit of the predictor characteristic or the value of the predictor characteristic at which the upper prediction boundary corresponding to the regression model intersects the upper specification limit for the first remaining article characteristic.

69. The computer program product of claim 39 wherein the instructions are further operable to cause the programmable processor to:

repeat the determine the regression model, receive the specification limits, locate the compliance area, locate the bounded regression area, and identify the relationship operations for all desired remaining article characteristics.

70. The computer program product of claim 69 wherein the instructions are further operable to cause the programmable processor:

to display the identified relationships.

71. The computer program product of claim 69 wherein the instructions are further operable to cause the programmable processor to:

store the identified relationships in a data structure.

72. A computer program product, physically stored on a machine-readable medium, for facilitating a determination of the magnitude and direction by which a pre-process characteristic would have to be adjusted to achieve a given design target, comprising instructions operable to cause a programmable processor to:

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

select a predictor characteristic from the plurality of article characteristics;

determine the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics,

receive the target values for the predictor characteristic and the first remaining article characteristic;

compute, based on the regression model, the value of the first remaining article characteristic at the target value of the predictor characteristic;

determine the magnitude and direction of the offset for the first remaining article characteristic by computing the difference between the computed value of the first remaining article characteristic and the target value of the first remaining article characteristic;

store the magnitude and direction of the offset in a data structure in association with an identifier for the first remaining article characteristic; and

repeat the computing, determining and storing operations for all desired remaining characteristics.

73. The computer program product of claim 72 wherein the instructions are further operable to cause the programmable processor to:

display the resulting magnitudes and directions of the offsets in association with the corresponding remaining article characteristics.

74. A computer program product, physically stored on a machine-readable medium, for facilitating analysis of the achievable gains in operating range associated with relaxing design tolerances corresponding to at least one article characteristic, comprising instructions operable to cause a programmable processor to:

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

select a predictor characteristic from the plurality of article characteristics;

determine the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics, wherein the regression model includes lower and upper prediction boundaries;

receive lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;

compute, based on the regression model, the minimum and maximum predictor characteristic values at which the first remaining article characteristic remains within the lower and upper specification limits of the first remaining article characteristic;

repeat the determining, receiving, and computing operations for all desired remaining article characteristics;

create a most constraining minimum predictor characteristic list by ranking the remaining article characteristics by the respective minimum predictor characteristic values associated therewith; and

starting with the remaining article characteristic associated with the greatest minimum predictor characteristic value;

compute the individual gain in operating range achieved by relaxing the applicable specification limit of the remaining article characteristic to the value corresponding to the minimum predictor characteristic value associated with the next remaining article characteristic in the ranked list;

compute the cumulative gain associated with relaxing the applicable specification limit of the corresponding article characteristic; and

repeat the first and second computing operations for all desired remaining article characteristics.

75. The computer program product of claim 74 wherein the instructions are further operable to cause the programmable processor to:

create a most constraining maximum predictor characteristic list by ranking the remaining article characteristics by the respective maximum predictor characteristic values associated therewith; and

starting with the remaining article characteristic associated with the lowest maximum predictor characteristic value;

compute the individual gain in operating range achieved by relaxing the applicable specification limit of the remaining article characteristic to the value corresponding to the maximum predictor characteristic value associated with the next remaining article characteristic in the ranked list,

compute the cumulative gain associated with relaxing the applicable specification limit of the corresponding article characteristic; and

,

repeat the first and second computing operations for all desired remaining article characteristics.

76. The computer program product of claim 75 wherein the instructions are further operable to cause the programmable processor to:

receive a selection of at least one remaining article characteristic from either or both of the most constraining minimum or maximum predictor characteristic list;

if the selection includes a remaining article characteristic from the most constraining minimum predictor characteristic list, then;

set the minimum predictor characteristic value to the minimum predictor characteristic value corresponding to the next article characteristic in the most constraining minimum predictor characteristic list, and

for all article characteristics in the most constraining minimum predictor characteristic list up to the selected article characteristic, compute the new lower or upper specification limit for the article characteristic; and

if the selection includes a remaining article characteristic from the most constraining maximum predictor characteristic list, then;

set the maximum predictor characteristic value to the maximum predictor characteristic value corresponding to the next article characteristic in the most constraining maximum predictor characteristic list, and

for all article characteristics in the most constraining maximum predictor characteristic list up to the selected article characteristic, determine the new lower or upper specification limit for the article characteristic.