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If, as in this case, the samples do not reflect the actual process profile, ignore this metric.

The number of distinct categories is related to the standard deviation of the chosen samples.

Note: For this column to be shown, you must enter the tolerance band or width.

% tolerance of 15.12% is well below the desired limit of 20% and you can use your measurement system to safely sort products into good and bad categories.

When %SV is significantly different than SV/Process, as in the case above, the chosen sample of parts does not mimic the profile of the actual process and %SV is unreliable.

Note: For this column to appear, you must enter a historical estimate of the standard deviation. However, using the historical estimate of the process standard deviation, a % process of 43.2% tells us that the measurement system is not acceptable to evaluate process improvements.With a value less than the suggested maximum limit of 30%, this value is marginally acceptable. % study variation is the ratio of the standard deviation of the measurement system divided by the standard deviation of the sampled parts.You must enter tolerance to calculate this metric. Note: In a gage R&R study, tolerance is defined as the difference between the upper and lower specification limits. If you want to evaluate whether the gage system is acceptable for inspection purposes, use % tolerance.(For example, if you pulled from production all parts that exceeded the upper specification limit in the study, the standard deviation of those parts would likely be very small compared to that of the entire process.) If you use % study variation to validate your measurement system, you must first verify the study samples mimic the actual process profile.The difference is % study variation uses the standard deviation of the sampled parts as the estimate of the process standard deviation while % process requires a user-entered estimate (historical) of the process standard deviation. Both metrics evaluate the ratio of the standard deviation of the measurement system to the standard deviation of the total process. The key metrics are, therefore, % study variation (%SV) or % process (SV/Process).Rather, its purpose is to discover whether the measurement system can see the process clear enough so, if you make a change, that change will be visible (Is it acceptable for process improvement activities-that is, DMAIC?).

The main purpose of measurement systems analysis in the context of a process improvement project (Six Sigma, DMAIC, and so on) is not to determine whether the measurement system can sort good from bad (Is it acceptable for inspection purposes?).

30% - The measurement system is unacceptable and should be improved.

Typical standards for %R&R (% study variation, % tolerance, and % process) are:.

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