Gage RR acceptance criteria.

Hai Paul,
Historical Sigma is under options so it is Optional. If you use it (Xor the Tolerance) Minitab calculates an extra column for you where the % are calculated with Sigma(process) in the denominator (instead of Sigma(data encountered) ). This column can tell you how good your gage system is in reference to the production Xor Customer specs instead of in reference to the data that you used during the analysis (needed when you can’t use representative data for your analysis). So Answer1 = Yes
Answer2: Standards are:

Ford: gage r&R% <10% for perfect; <30% for acceptable; otherwise: do a GB project on the Gage System first.
gage r&R % <15% for OK.
The gage r&R value can be found in the Session Window output of gage r&R in the column (%SV) the first(=upper) value.
I can see no reason to change the 5.15 into a 1. Maybe you remember it wrongly: some teachers say you should change it into 6. Minitab14 uses 5.15 as Default; Minitab15 uses 6. The 5.15 (or 6) has to do with changing Sigma-values into Range-values and is an approximation anyway. The 5.15 corresponds with 99% and the 6 with 99.7% of the data being within the covered Range (100% is unreachable because the Normal Distribution is an infinite distribution).
And remember: the gage r&R is not an investigation of the equipment only!
Hope this helps

You are not current – it changed about a decade ago.

Hai Paul,
both questions relate to the issue of ‘Representativeness’. And the answers are: it depends.
Remember: when you do an analysis the conclusion is only valid ON THE DATA YOU USED. Generally you try to make the data you use a representative sample of your population. And then you decide that the conclusions on your sample are also valid for your population. With Confidence Interval you can also take into account the probability of being (a bit) wrong due to sample variation (i.e. how correct will you be in your predictions).
And remember: data from production is not necessarily representative for ALL production (you could have data in a smaller range or with special causes or without,..).
Only YOU can decide whether the data you use is representative and if the conclusion is valid for your population. In the gage r&R there is an option to correct a wrong Range (data-range population range): The Tolerance option.
Another issue is: does the measurement system work in the same way for all the products (also those out of specs). An example is a machine which not only measures but also tweakes the product into spec if it is very close to the specs. In fact the eqt is then not only a measuring machine but also a repair machine (=production process).
 
hope this helps

Paul, here’s the correct info. I verified the facts having just referenced the 3rd and 4th editions of the AIAG MSA manuals: 5.15 is used because it represents 99% of the area under the normal curve. This is stated in the manual. When you use the calculations sheet in the (current) 4th edition it has a footnote that says see the 3rd edition for an explanation of the 5.15 constant. The 3rd edition has a loose leaf errata attachment for corrections to the book. It says the reference to page iv should have been vi. On page vi you will find the explanation that 5.15 had always historically been the constant used for 99% of the area under the curve. It does not say the constant was changed. But it does go on to say that you “may wish to use 6.0”. It further explains that if you do use 6.0, you should make it clear to people how you are doing the calculations.