Manufacturing design and process analysis system
First Claim
1. A method facilitating design, manufacturing, and other 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;
determining 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 receiving lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;
locating, 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;
locating 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
identifying the relationship between the bounded regression area and the compliance area.
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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.
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Citations
38 Claims
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1. A method facilitating design, manufacturing, and other 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;
determining 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 receiving lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;
locating, 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;
locating 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
identifying the relationship between the bounded regression area and the compliance area. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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34. A method 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
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;
determining the regression model between the predictor characteristic and a first remaining article characteristic in the plurality of article characteristics, receiving the target values for the predictor characteristic and the first remaining article characteristic;
computing, based on the regression model, the value of the first remaining article characteristic at the target value of the predictor characteristic;
determining 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;
storing the magnitude and direction of the offset in a data structure in association with an identifier for the first remaining article characteristic; and
repeating the computing, determining and storing steps for all desired remaining characteristics. - View Dependent Claims (35)
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36. A method facilitating analysis of the achievable gains in operating range associated with relaxing design tolerances corresponding to at least one article characteristic, 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;
determining 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;
receiving lower and upper specification limits for the predictor characteristic and the first remaining article characteristic;
computing, 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;
repeating the determining, receiving, and computing steps for all desired remaining article characteristics;
creating 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;
computing 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;
computing the cumulative gain associated with relaxing the applicable specification limit of the corresponding article characteristic; and
repeating the first and second computing steps for all desired remaining article characteristics. - View Dependent Claims (37, 38)
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Specification