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US5715181A Expired / Lapsed US ⏱️ 0.0 years remaining

Isogrammetric analysis method for high-yield processes

Assignee: Individual
•
Filing: 1995-04-03
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Granted: 1998-02-03
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Expires: 2015-04-03
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Abstract

Abstract A method is provided for process monitoring by statistical measurement of level-of-defectives performance in manufacturing and other processes. Statistical performance data functions of mean-value shift and deviation ratio are plotted on an isogrammetric chart for off-line analysis or, alternatively, are entered into a computer that has been programmed with the isogrammetric format. The resultant information revels the probable process yield and is useful to certify quality of performance in direct terms of level of defectives being produced. The method is particularly useful for high-yield processes where statistical sampling and inspection methods tend to miss the relatively few defectives and statistical process control (SPC) criteria appear to indicate that a manufacturing process is "in control".

Inventors

  • 👤 Robert L. Horst

Bibliographic Details

Application Number —
Jurisdiction US
Data Source google_patents
Last Synchronized 2026-11-06 04:48
CPC Classifications
H; H10; H10P; H10P74/00; H10P74/23

Claims Analysis

Total Claims: 12
Claim 1
Independent Claim 134 words
A method for monitoring and analyzing data for a process comprising the steps of: (a) establishing specification target values, (b) (acquiring)measuring said process to acquire data of a variable measured during a measuring operation and calculating off-line the statistical process control metrics mean-value and standard deviation which represent a variation of said data, (c) comparing said calculated statistical metrics to specification target values and permitted variations to calculate mean-value shift and ratio of design tolerance to standard deviation, (d) plotting instantaneous or time-averaged values of mean-value shift and ratio of design tolerance to standard deviation on an isogrammetric representation consisting of a spatial array of lines of constant defect-level performance based on statistical isograms for constant quality-of-performance criteria, and (e) providing statistical level-of-defectives/defaults/failures performance measurement directly from isogrammetric representation coordinates of the plotted values.
Claim 2
Independent Claim 134 words
A method for monitoring and analyzing data for a process comprising the steps of: (a) establishing specification target values, (b) (acquiring)measuring said process to acquire data of a variable measured during a measuring operation and calculating off-line the statistical process control metrics mean-value and standard deviation which represent a variation of said data, (c) comparing said calculated statistical metrics to specification target values and permitted variations to calculate mean-value shift and ratio of design tolerance to standard deviation, (d) plotting instantaneous or time-averaged values of mean-value shift and ratio of design tolerance to standard deviation on an isogrammetric representation consisting of a spatial array of lines of constant defect-level performance based on statistical isograms for constant quality-of-performance criteria, and (e) providing statistical level-of-defectives/defaults/failures performance measurement directly from isogrammetric representation coordinates of the plotted values.
Claim 3
Independent Claim 315 words
A method for monitoring and adjusting a high-yield manufacturing process which produces a product, said method comprising the steps of: (a) establishing specification target values and permitted variations of ideal product and process variable readings and design specifications for desired high yield level-of-defectives performance, (b) measuring with sensors subgroups of process raw data of said product or process variable readings during a manufacturing process and then calculating the statistical process control metrics mean-value and standard deviation which represent a data variation from said specification target values, (c) comparing said calculated statistical process control metrics for said data subgroups of process raw data to said specification target values and permitted variations of ideal product and process variable readings to calculate the mean-value shift from said specification target values and permitted variations and to calculate the ratio of design tolerance to actual standard deviation for each product or process variable, (d) plotting the values of said mean-value shift and said ratio of design tolerance to actual standard deviation for each subgroup of process raw data on an isogrammetric representation consisting of a spatial array of data coordinates defining lines of constant defect-level performance based on statistical isograms for constant quality-of-performance criteria, (e) calculating for a plurality of subgroups of process raw data, either individually or averaged together, the statistical level-of-defective product or process performance values directly from said representation, (f) displaying statistical level-of-defectives performance calculated values for at least one subgroup of said subgroups of process raw data on a medium showing performance isograms including the isogram representing the specification target value for level-of-defectives performance, and (g) performing necessary process adjustments or shutting down the manufacturing process in response to said level-of-defectives performance calculated values as necessary to reduce product or process defectives and increase process product yield, wherein said step of performing process adjustments or shutting down the manufacturing process is performed by a process operator.
Claim 4
Independent Claim 315 words
A method for monitoring and adjusting a high-yield manufacturing process which produces a product, said method comprising the steps of: (a) establishing specification target values and permitted variations of ideal product and process variable readings and design specifications for desired high yield level-of-defectives performance, (b) measuring with sensors subgroups of process raw data of said product or process variable readings during a manufacturing process and then calculating the statistical process control metrics mean-value and standard deviation which represent a data variation from said specification target values, (c) comparing said calculated statistical process control metrics for said data subgroups of process raw data to said specification target values and permitted variations of ideal product and process variable readings to calculate the mean-value shift from said specification target values and permitted variations and to calculate the ratio of design tolerance to actual standard deviation for each product or process variable, (d) plotting the values of said mean-value shift and said ratio of design tolerance to actual standard deviation for each subgroup of process raw data on an isogrammetric representation consisting of a spatial array of data coordinates defining lines of constant defect-level performance based on statistical isograms for constant quality-of-performance criteria, (e) calculating for a plurality of subgroups of process raw data, either individually or averaged together, the statistical level-of-defective product or process performance values directly from said representation, (f) displaying statistical level-of-defectives performance calculated values for at least one subgroup of said subgroups of process raw data on a medium showing performance isograms including the isogram representing the specification target value for level-of-defectives performance, and (g) performing necessary process adjustments or shutting down the manufacturing process in response to said level-of-defectives performance calculated values as necessary to reduce product or process defectives and increase process product yield, wherein said step of performing process adjustments or shutting down the manufacturing process is performed by a process operator.
Claim 5
Dependent Claim 54 words
The method for monitoring and adjusting a high-yield process as set forth in claim 2 further comprising a step of relating said level-of-defectives performance to yield of the high-yield process wherein 3 defects per million equals 99.9997 percent yield and level of defects ranges to 200 defects per thousand which equals 80 percent yield.
Claim 6
Dependent Claim 38 words
The method for monitoring and adjusting a high-yield process as set forth in claim 2 wherein said step of plotting values on an isogrammetric representation is performed manually and further wherein said isogrammetric representation is a graphical chart.
Claim 7
Dependent Claim 38 words
The method for monitoring and adjusting a high-yield process as set forth in claim 2 wherein said step of plotting values on an isogrammetric representation is performed manually and further wherein said isogrammetric representation is a numerical chart.
Claim 8
Dependent Claim 40 words
The method for monitoring and adjusting a high-yield process as set forth in claim 3 wherein said step of plotting values on an isogrammetric representation is performed using a computer and further wherein said isogrammetric representation is a data base.
Claim 9
Dependent Claim 32 words
The method for monitoring and adjusting a high-yield process as set forth in claim 6 wherein said step of measuring raw process data is performed automatically by sensors connected to a processor.
Claim 10
Dependent Claim 31 words
The method for monitoring and adjusting a high-yield process as set forth in claim 7 wherein said step of displaying on a medium is performed using a graphical display or printout.
Claim 11
Dependent Claim 31 words
The method for monitoring and adjusting a high-yield process as set forth in claim 7 wherein said step of displaying on a medium is performed using a numerical display or printout.
Claim 12
Dependent Claim 33 words
The method for monitoring and adjusting a high-yield process as set forth in claim 7 wherein said step of calculating the statistical level-of-defective product or process values is performed automatically using a processor.

References Cited (Backward Citations)

US5134574A Cited
US5245554A Cited
US5257206A Cited
US5339257A Cited
US5311759A Cited
US5440478A Cited

USPTO Annuity & Maintenance Windows

Annuity Stage Window Opens Payment Deadline Surcharge Period Until Estimated Fee Status
3.5 Years (Year 4) 2001-02-02 2001-08-04 2002-02-03 $2000.00 Window Closed / Lapsed
7.5 Years (Year 8) 2005-02-02 2005-08-04 2006-02-03 $3760.00 Window Closed / Lapsed
11.5 Years (Year 12) 2009-02-02 2009-08-04 2010-02-03 $7700.00 Window Closed / Lapsed

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