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I have a composite position called out on a set of features (x2)
The ABC datum is pretty is a pretty straight forward Plane, Diameter, Slot, so no issues there.
The feature(s) are two threaded cylinders that are in line with each other, but separated by a distance of about 60mm.
Right now, I'm reporting the position to within 0.3, to ABC 2x (one for each location), but wondering if this should be reported as a single feature.
My big question is the position callout at the lower level, of 0.1 with no datums called out. I feel that I understand the basic intent (keeping the two features in line to each other), but not sure how to program in the callout.
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Keith,

The Position tolerance with no datum is just the position of one to the other. To report it, choose either one as the datum and report the position of the other.
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Thanks Jacob, that confirms what I was thinking, but I guess I was hoping for a different answer 🤣
My positional result comes out to 0.68, which clearly exceeds the tolerance; but, when I recall both threaded features into a single cylinder, I get a Cylindricity of 0.06. I'm guessing that I'm getting the position so far out of tolerance, because there are only 3 full threads available to establish the cylinder 🙄
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Since I usually don't scan the PD of threads (I typically use Pos Pins)
Regarding Scanning the pitch diameter of a thread, which is also a datum feature:

What do you all suggest for Evaluation Method, Filters, and Outliers?
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I usually scan the Major Dia., for which I would use a minimum circumscribed/max inscribed element. I use the largest probe tip that I can and I make sure to take a very high number of points to guarantee that the high spots are obtained.

As far as your result being so high - It could be due to the threaded cylinder, it could be due to one being the primary datum vs. the other (projection error), or possibly that you are not obtaining the desired points. I would think a LSQ/minimum evaluation would be best to capture the pitch dia.
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If you are going to scan linear lines, I've found huge success in increasing the point density really high, and in the outlier elimination setting it to a 1/3 outlier with a 3 iteration loop.
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