If you’ve done or plan to do process improvement work, then you’ve probably asked yourself whether you’re really getting precise enough measurements. You must trust your data before using it to make critical decisions about adjustments and resource allocation. Measurement systems analysis (MSA) broadly refers to procedures that estimate and evaluate the amount of variation in a measurement system. One type is an EMP study, also known as Wheeler’s Method. EMP stands for Evaluate Measurement Process.
If you’ve done or plan to do process improvement work, then you’ve probably asked yourself whether you’re really getting precise enough measurements. You must trust your data before using it to make critical decisions about adjustments and resource allocation. Measurement systems analysis (MSA) broadly refers to procedures that estimate and evaluate the amount of variation in a measurement system. One type of is an EMP study, also known as Wheeler’s Method. EMP stands for Evaluate Measurement Process. The EMP study evaluates two sources of measurement variation:
Repeatability: The variation that is observed when the same operator measures the same part many times, using the same gage, under the same conditions.
Reproducibility: The variation that is observed when different operators measure the same part many times, using the same gage, under the same conditions.
For example, a manufacturer of consumer foods monitors fill weights of cereal boxes. The manufacturer wants to make sure that the variation from different measurements is small enough that they can use other process improvement analyses. The results from an EMP study help to determine if the measurement system is acceptable and how to improve the measurement system.
The EMP statistics provide the measurement system with its classification. In these results, the classification is First Class. The team can be confident that the measurement system will be good enough to use for other process improvement activities.
The EMP study also includes information that you can use to decide when to prioritize improvements to the measurement system. The Analysis of Mean Ranges (ANOMR) and the Analysis of Main Effects (ANOME) show where the reproducibility is low relative to the process variation. In this ANOMR, operator B is less consistent than the other two operators. Improving the consistency for operator B will improve the measurement system.
In this example ANOME, different operators tend to measure higher or lower than each other. Improvements that bring the mean measurements of different operators closer will improve the measurement system.
To act on your data, you need to trust that the data are right. The EMP study in Minitab Statistical Software gives you the power to see whether your measurement system is acceptable and how to improve your measurement systems. When you assess the precision of your measurements, you can have confidence that everything that follows is built from data that you can trust.