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Select Analyze > Quality and Process > Measurement Systems Analysis.
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Notice that the MSA Method is set to EMP, the Chart Dispersion Type is set to Range, and the Model Type is set to Crossed.
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Click OK.
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Figure 7.8 Average and Range Charts
Take a closer look for interactions between operators and parts. From the red triangle menu next to Measurement Systems Analysis for Y, select Parallelism Plots.
Figure 7.9 Parallelism Plot
Take a closer look at the variance between operators. From the red triangle menu next to Measurement Systems Analysis for Y, select Test-Retest Error Comparison.
Figure 7.10 Test-Retest Error Comparison
Figure 7.11 Bias Comparison
Figure 7.12 EMP Results
Use the Shift Detection Profiler to explore the probability that a control chart will be able to detect a change in your process. From the red triangle menu next to Measurement Systems Analysis for Y, select Shift Detection Profiler.
Figure 7.13 Shift Detection Profiler
Explore your ability to detect a shift in the mean of two part standard deviations in the 10 subgroups following the shift. Click the Part Mean Shift value of 2.1701 and change it to 4.34 (2.17 multiplied by 2). The probability of detecting a shift of twice the part standard deviation is 56.9%.
Next, see how eliminating bias affects your ability to detect the shift of two part standard deviations. Change the Bias Factors Std Dev value from 1.1256 to 0. The probability of detecting the shift increases to 67.8%.
You can also explore the effect of using a control chart based on larger subgroup sizes. For subgroup sizes of two or more, the control chart is an X-bar chart. Change the Bias Factors Std Dev value back to 1.1256 and deselect all but the first test. Set the Subgroup Size in the profiler to 4. The probability of detecting the two part standard deviation shift is 98.5%.
Finally, see how well your measurement increments are working. From the red triangle menu next to Measurement Systems Analysis for Y, select Effective Resolution.
Figure 7.14 Effective Resolution