A plot of the average measurement values for each combination of the part and X variables. The Average Chart helps you detect product variation despite measurement variation. In an Average Chart, out of control data is desirable because it detects part-to-part variation. See Average Chart.
A plot of the variability statistic for each combination of the part and X variables. Appears only if you selected Range as the Chart Dispersion Type in the launch window. The Range Chart helps you check for consistency within subgroups. In a Range Chart, data within limits is desirable, indicating homogeneity in your error. See Range Chart or Standard Deviation Chart.
A plot of the standard deviation statistic for each combination of the part and X variables. Appears only if you selected Standard Deviation as the Chart Dispersion Type in the launch window. The Standard Deviation Chart helps you check for consistency within subgroups. In a Standard Deviation Chart, data within limits is desirable, indicating homogeneity in your error. See Range Chart or Standard Deviation Chart.
a report that computes several statistics to help you assess and classify your measurement system. See EMP Results.
an Analysis of Means chart for testing if the X variables have different averages. See Bias Comparison.
an Analysis of Means for Variances or Analysis of Means Ranges chart for testing if any of the groups have different test-retest error levels. See Test-Retest Error Comparison.
an interactive set of charts that you can adjust to see the probabilities of getting warnings on your process behavior chart. See Shift Detection Profiler.
Note: This report is similar to the Variance Components report in the Variability Chart platform, except that it does not compute Bayesian variance component estimates. For more information, see Variance Components in Variability Gauge Charts.
Note: This report is similar to the Gauge R&R report in the Variability Chart platform, except that the calculation for Reproducibility does not include interactions. For more information about Gauge R&R studies, see About the Gauge R&R Method in Variability Gauge Charts.
draws the overall mean of the Y variable on the chart.
draws vertical lines to delineate between the X variables.
draws vertical lines to delineate between the X variables.
Note: The statistics in this report are based on ranges in the following instances: if you selected EMP as the MSA Method and Range as the Chart Dispersion Type, and you have a one factor or a two factor, balanced, crossed model. Otherwise, the statistics in this report are based on variances.
the median error for a single measurement. Indicates the resolution quality of your measurement and helps you decide how many digits to use when recording measurements. For more information, see Effective Resolution.
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Intraclass Correlation (no bias) does not take bias or interaction factors into account when calculating the results.
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Intraclass Correlation (with bias) takes the bias factors (such as operator, instrument, and so on) into account when calculating the results.
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Intraclass Correlation (with bias and interaction) takes the bias and interaction factors into account when calculating the results. This calculation appears only if the model is crossed and uses standard deviation instead of range.
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Tip: To prevent the legend from appearing, deselect Show Monitor Classification Legend in the EMP Measurement Systems Analysis platform preferences.
Shift Detection Profiler for Gasket.jmp shows the Shift Detection Profiler report for the Gasket.jmp sample data table, found in the Variability Data folder.
Often, parts for an MSA study are chosen to have specific properties and do not necessarily reflect the part-to-part variation seen in production. For this reason, you can specify the in-control part standard deviation by selecting Change In-Control Part Std Dev from the Shift Detection Profiler red triangle menu.
For a subgroup of size n, control limits are set at the following values:
to account for the assumption that the reproducibility factors are constant within a subgroup.For more information about the Variance Components report, see Variance Components in Variability Gauge Charts.
The number of subgroups over which the probability of a warning is computed. If the number of subgroups is set to k, the profiler gives the probability that the control chart signals at least one warning based on these k subgroups. The Number of Subgroups is set to 10 by default. Drag the vertical line in the plot to change the Number of Subgroups.
This panel gives a brief description of four of the Shift Detection Profiler settings. For further details, see Shift Detection Profiler Settings.
Tip: To prevent the legend from appearing, deselect Show Shift Detection Profiler Legend in the EMP Measurement Systems Analysis platform preferences.
In the Customize and Select Tests panel, select and customize the tests that you want to apply to the k subgroups in your control chart. The eight tests are based on Nelson (1984). For more details about the tests, see Tests in Control Chart Builder.
If no settings have been saved to preferences, this option resets the selected tests to the first test only. The values of n are also reset to the values described in Tests in Control Chart Builder. If settings have been saved to preferences, this option resets the selected tests and the values of n to those specified in the preferences.
Note: You can access preferences for control chart tests by selecting File > Preferences> Platforms > Control Chart Builder. Custom Tests 1 through 8 correspond to the eight tests shown in Customize and Select Tests.
Saves the selected tests and the values of n for use in future analyses. These preferences are added to the Control Chart Builder platform preferences.
The Bias Comparison option creates an Analysis of Means chart. This chart shows the mean values for each level of the grouping variables and compares them with the overall mean. You can use this chart to see whether an operator is measuring parts too high or too low, on average.
select an option from the most common alpha levels or specify any level using the Other selection. Changing the alpha level modifies the upper and lower decision limits.
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Show Decision Limits draws lines representing the Upper Decision Limit (UDL) and the Lower Decision Limit (LDL) and defines those values.
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Show Decision Limit Shading adds shading between the UDL and the LDL.
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Show Center Line draws the center line statistic that represents the average.
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Point Options changes the chart display to needles, connected points, or points.
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The Test-Retest Error Comparison option creates a type of Analysis of Means for Variances or Analysis of Means Ranges chart. This chart shows if there are differences in the test-retest error between operators. For example, you can use this chart to see whether there is an inconsistency in how each operator is measuring. The Analysis of Mean Ranges chart is displayed when ranges are used for variance components.
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