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Default Math vs. Least Squares

Vantage
I have a part that uses 2 cylinders as a common datum. There are multiple features positioned back to the common A-B datum. Using the default math algorithm and the simultaneous tolerance command I get all but one feature to pass. This feature is a diagonal through hole that is controlled in the X direction by a linear dimension and then in Y and Z by the cylindrical datum. Now if I change the datum math to least squares on just this feature it gives me a very good position. I am assuming this is not the correct way unless I change all the other related features to least squares datum math as well. But if I do the other features that were really good position wise with the default datum math now were failing.
I didn't mention that the 2 common datum cylinders also get ground to their final size later after the complete part is made.

Just wondering what you all think would be the best way to evaluate these features and if you can just have least squares math for one but default for the rest of the related positions.

Thanks all.
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  • I guess I should have specified Default vs. Least Squares math in GeoTol, and if changing one feature in a simultaneous call out to least squares for the datum math would be kosher or not.
  • in reply to Vantage
    It depends on how tight the size & form tolerance is for the datums, your point spacing / hit density and how accurate your CMM & sensor is. If you read the detailed information in the help files it explains that for cases where the uncertainty of your system is close to or exceeding the expected form values, it may be advantageous to use LSQ. This is generally the case for laser measurements for example, where there is a comparatively large uncertainty (when compared to other sensors) and high point density. This combination of "noise" in the data and high numbers of points can lead to longer calculation times and less repeatable results if DEFAULT math is chosen. LSQ will average out the noise, leading to more repeatable results and generally yields faster calculation times because it does not have to iterate through all the hits trying to optimize the fit.

    Ultimately, there is no exact answer we can give you. You need to perform your own tests to determine what is acceptable for the types of features you are measuring and how your particular system behaves.

    Obviously, if you want to fully comply to the standards you need to select DEFAULT because that is what the standards define.
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  • in reply to Vantage
    It depends on how tight the size & form tolerance is for the datums, your point spacing / hit density and how accurate your CMM & sensor is. If you read the detailed information in the help files it explains that for cases where the uncertainty of your system is close to or exceeding the expected form values, it may be advantageous to use LSQ. This is generally the case for laser measurements for example, where there is a comparatively large uncertainty (when compared to other sensors) and high point density. This combination of "noise" in the data and high numbers of points can lead to longer calculation times and less repeatable results if DEFAULT math is chosen. LSQ will average out the noise, leading to more repeatable results and generally yields faster calculation times because it does not have to iterate through all the hits trying to optimize the fit.

    Ultimately, there is no exact answer we can give you. You need to perform your own tests to determine what is acceptable for the types of features you are measuring and how your particular system behaves.

    Obviously, if you want to fully comply to the standards you need to select DEFAULT because that is what the standards define.
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