% of Tolerance or % of Study Variation Results Here is the criteria for determining if your measurement system is adequate, using the different % calculations in Minitab (derived and influenced from AIAG guidelines for the gage R&R table, but not the exact same conclusions). The good chart below that shows a very small blue bar, which means the measurement system takes up very little variation, compared to the spec limits of the item being measured. In the examples above, the far left group of charts shows a blue bar above the 50% mark. If the % is less than 10%, then I have an adequate measurement system. I would then look at whether the repeatability or reproducibility % was greater, in order to determine what I need to improve. If that number is greater than 30%, then I have a problem with my system. Others use ‘% of StudyVar’ (green) or ‘% of Contribution’ (orange) This provides me with a quick assessment of the measurement system. The first place I look is the R&R variation as a % of Tolerance (blue). ![]() There are three comparisons made from these results: % of overall variation (StudyVar), % of Tolerance (Spec Limit width, if specifications are applicable for this measurement), and % of Contribution. The first chart (upper left corner) is your breakdown of variation, into Part, Repeatability, and Reproducibility. ![]() If the results are bad, then they will guide you to see where there are opportunities to improve. If the results are good, then the charts will show you why they’re good. The upper left chart will be a summary of the data analysis above, and the rest of the charts will slice-and-dice the data to help support the results. Next, we can look graphically at the charts in Minitab for deeper understanding and troubleshooting (if necessary). If you extract these numbers from the analysis tables above, and review it against the criteria, you can see why Tab Width is deemed “BAD” (unacceptable measurement system), and Cap Bow is deemed “GOOD” (acceptable measurement system). If you have below 5, then it needs improvement and would be considered unacceptable. If you have between 5 and 10, that’s considered marginal (still acceptable, but could use improvement). The goal is to have a NCD of 10 or greater. If they fall within the same “bucket” then we cannot tell those items apart from each other. To have more accuracy and precision in our measurements, we want to have many different buckets, which allow us to tell one item from another. Think about these as “buckets” in which your measurement system can group your data. The number of distinct categories also represents the number of groups within your process data that your measurement system can discern. Note: Not every measurement has specification limits, so % Tolerance may not be applicable, but % Study Variation will also be calculated. There are some exceptions to this, depending on how capable the measurement is within the specifications, which we’ll discuss below. We will discuss this criteria in the sections below, but basically you want these numbers to be less than 10% ideally, but no greater than 30%. Total Gage R&R %Study Var and Total Gage R&R %Tolerance Anything between 1 and 9% would be considered marginal. The criteria is to have less than 1% of the variation due to Total Gage R&R, and no more than 9%. These percentages are related closely to the % for Repeatability and Reproducibility in other tables, but they sum up to 100% (where the other ones do not sum to 100%, which is confusing for many). % Contribution is the percentage of overall variation from each variance component: Repeatability, Reproducibility (Operator and Operator*Samples) and Part-to-Part variation. ![]() We look at 4 criteria to determine how good the Gage R&R results are: Here are the main results for the Minitab data analysis, shown as a summary table. ![]() Minitab will generate both data analysis tables along with graphs. In this article, we will look at two different examples, one for measuring TAB WIDTH (poor results), and the other measuring CAP BOW (good results) However, there is some confusion and a lack of knowledge on how to interpret each chart, in order to better understand the validity of your measurement system. Minitab provides a great Gage R&R Sixpack (6 sections) report, when performing a measurement systems analysis (MSA) study.
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