Web-based system of product performance assessment and quality control using adaptive PDF fitting
First Claim
1. A method comprising:
- receiving data for a product;
fitting the data with a plurality of probability density functions (PDFs);
selecting a PDF that best fits the data;
generating one or more performance capability parameters for the product based on the best fitting PDF;
generating a report that presents at least one of the performance capability parameters; and
adjusting statistical control limits for the product based on the data, wherein adjusting statistical control limits comprises;
generating a first set of data samples using the selected PDF,calculating new control limits from the first set of data samples,generating a second set of data samples,determining an average run length (ARL) value from the second set of data samples and the new control limits, andcomparing the determined ARL value to an acceptable ARL value.
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Abstract
A data analysis system analyzes data sets that are characterized by a wide variety of probability density functions (PDFs), and also analyzes mixed populations, i.e., a single data set containing subsets of data that each fit a different distribution. The data analysis system receives quality control data from a product manufacturing or product testing floor, determines whether the data is a mixed population, and fits the data with a variety of PDFs. The data analysis system selects the best fitting PDF based on statistical characteristics calculated for each fitted PDF. The data analysis system generates performance capability parameters based on the best fitting PDF, and may generate reports illustrating the performance capability parameters. The data analysis system also adjusts statistical control limits to provide a more reliable process trigger and control plan. In this manner, the data analysis system may more accurately report product performance.
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Citations
32 Claims
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1. A method comprising:
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receiving data for a product; fitting the data with a plurality of probability density functions (PDFs); selecting a PDF that best fits the data; generating one or more performance capability parameters for the product based on the best fitting PDF; generating a report that presents at least one of the performance capability parameters; and adjusting statistical control limits for the product based on the data, wherein adjusting statistical control limits comprises; generating a first set of data samples using the selected PDF, calculating new control limits from the first set of data samples, generating a second set of data samples, determining an average run length (ARL) value from the second set of data samples and the new control limits, and comparing the determined ARL value to an acceptable ARL value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A system comprising:
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a data acquisition module that acquires data for a product; a probability density function (PDF) fitting module that fits the data with a plurality of PDFs, selects a PDF that best fits the data, and generates one or more performance capability parameters for the product based on the best fitting PDF; a report generator that generates a report that presents at least one of the performance capability parameters; and a control limit determination module that generates a first set of data samples using the selected PDF, calculates new control limits from the first set of data samples, generates a second set of data samples, determines an average run length (ARL) value from the second set of data samples and the new control limits, and compares the determined ARL value to an acceptable ARL value. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24)
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25. A computer-readable medium comprising instructions for causing a processor to:
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receive data for a product; fit the data with a plurality of probability density functions (PDFs); select the PDF that best fits the data; generate one or more performance capability parameters for the product based on the best fitting PDF; generate a report that presents at least one of the performance capability parameters; generate a first set of data samples using the selected PDF; calculate new control limits from the first set of data samples; generate a second set of data samples; determine an average run length (ARL) value from the second set of data samples and the new control limits; and compare the determined ARL value to an acceptable ARL value. - View Dependent Claims (26, 27, 28, 29, 30, 31)
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32. A method comprising:
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receiving data for a product; fitting the data with a plurality of probability density functions (PDFs); selecting a PDF that best fits the data; generating one or more performance capability parameters for the product based on the best fitting PDF; generating a report that presents at least one of the performance capability parameters; automatically separating the data into two or more data sets when the data comprises two or more data distributions, wherein one of the data sets is a main distribution data set, wherein automatically separating the data into the two or more data sets comprises automatically separating the data into three data sets when the data comprises three data distributions, wherein the data sets comprise a main distribution, an upper tail section, and a lower tail section; fitting the main distribution data set with the plurality of PDFs; selecting a PDF that best fits the main distribution data set; determining a proportion of each of the lower tail section, the main distribution, and the upper tail section with respect to the data; and computing defects per opportunity (DPO) rates for each of the lower tail section and the upper tail section.
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Specification