| yieldPower | |||||||||||||||||||||
| Statistical Analysis | |||||||||||||||||||||
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Automated Test Equipment tests whether parts failed or passed a test. During the test process, large amounts of data are collected and saved for statistical analysis. By analyzing this data, production errors can be detected at an early stage and corrected accordingly. With yieldPower
it is possible to do statistical analysis on data, which is generated
by automated test equipment.
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Statistical
Process Control yieldPower
uses methods which are part of Statistical Process Control (SPC). SPC
allows users to analyze production information and apply those results
for production control. The combination of reading and analyzing ATE tester
data, combined with SPC analysis, makes yieldPower the ideal software
tool for the ATE industry. |
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| Using yieldPower for statistical analysis | |||||||||||||||||||||
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STDF and CSV Data
Input
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Showing Raw Data
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| Load a dataset into yieldPower and view its data in the raw data table. | |||||||||||||||||||||
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| With filter settings it is possible to select only important tests and have their results displayed. | |||||||||||||||||||||
| Outlier Detection | |||||||||||||||||||||
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Tests
are displayed one per row, with each die's results for the particular
test.
Outliers calculated using the Tukey Method are highlighted in red. Data is editable for outlier marking and changing of test results. |
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| Statistical Results | |||||||||||||||||||||
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Statistics
such as Mean, Median and Average, are calculated.
In addition typical Process Control values like Cp and Cpk are available. |
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