Variation (using ANOVA method) Required for Gage R&R

An argument about variation using ANOVA method - which one is "right"?
1) We need to dial in our blow molded product to the low end of the spec and the high end of the spec to ensure we have the whole range of variation the gage is required to measure.
2) Based on the capability study, control limits are calculated and the range between those calculations are used as the basis for the variation the gage needs to measure.
I'll admit, I'm the number 2 and I'm not the boss. The boss is dead set on number 1. Problem is, if we run to the low side on wall, we're out of spec on weight and run the risk of going out of spec on wall as well. Our charts show us running with a shifted (to the high side), albeit normal curve. (Why the print specs and tolerances weren't revisited before PPAP I have no idea!) I have a die setter ready to explode because he can't dial in what the QA Manager (and acting QE on this project) wants with out producing a bunch of junk - have I been doing this wrong the whole time? I never had a customer question it, or have a gage go haywire. But I'm stuck now with a whole bunch of frustrated program people over a MSA - and a looming PPAP date. Any suggestons?

Another quick "Bump". My Thanks in advance to anyone who can help with this one.

Take a look at my blog on R&R studies, particularly the section on part selection. This should fully answer your question.

While we are working out the issue , I am pasting the relevant section from my blog below.

Part Selection

The first step in an effective R&R study is to determine the use of the gage itself. Will it be used for part inspection to a tolerance, for process control, for statistical studies (e.g., a hypothesis test, capability study, DOE, etc.), or for a combination of these? This is very important because it influences the selection and quantity of parts needed for the R&R study.

If the gage is used solely for part inspection, the selection of parts is not critical because the part variation is not included in the calculation of the R&R metric, %Tolerance (i.e., P/T Ratio). Some will recommend that parts representing the full spread of the tolerance be used. While this does not hurt, it is not really necessary. If a gage linearity study has been performed, the change in bias over the tolerance spread is known. If a gage linearity study has not been performed and there is a linearity issue an R&R study will not detect it.

If the gage is used for part inspection or for statistical tests, the selection of parts is critical because the part variation is part of the calculation of the R&R metric, % Study Variation (i.e., %GRR). It is vital that the parts selected for the study reflect the actual variation of the process. That is, the StdDev of the parts equals the StdDev of the process. Some statistical packages, such as Minitab, allow the entry of the historical StdDev of the process. If your software has this option, use it, entering the process StdDev from a capability study or calculated from SPC charts. If the software does not have the feature, manual calculations using the historical value are still possible as follows"

% Study Variation = 100 * [StdDevR&R / StdDevTotal Variation]

StdDevTotal Variation = SQRT[StdDevR&R^2 + StdDevPart Variation^2]

Manually substitute the StdDev from a capability study for StdDevPart Variation