## Tip Radius Selection for Roundness

The measurement of roundness is often debated.

Many of these debates are centered around the tip radius and filtering used in the measurement.  This debate is further complicated by the fact that the typical roundness graph distorts reality.

Here is the same roundness data plotted at varying magnifications…

When we look at a roundness graph for an outside diameter measurement we see locally concave areas.  Often these areas look rather sharp.  This is due to the polar plot scaling and the magnification of “errors” rather than the magnification of the “size” .

The rightmost plot appears as though there are large concave areas on this component.  However, this data is from a precision gage ball.  The actual workpiece has no concave areas as the polar plot seems to indicate.  In fact the actual surface is completely convex and, given the magnitude of the roundness errors, a flat follower would have no problem measuring the roundness of this surface.

One other problem arises from a polar plot and it’s “vanishing point” at the center of the plot.  Since negative values all approach the center of the plot, they tend to “compress”.  Positive values tend to “fan out”.  This gives the perception that inward features are much sharper than outward features:

When we increase the scale, we see a large (apparent) difference between peak and valley curvatures:

On the right most graph (above) we get the perception that the valley bottom becomes a sharp point.  However, this is not the case with the actual data.

So let’s look at sine waves and think about the concept of “radius of curvature”…

Linear Sine Waves and their Radii

The radius of curvature of a sine wave (either peak or valley) is given by:

Where,

RSINE        the smallest radius of the sine wave (for example at the valley).  See Figure A4.

l             the wavelength of the sine wave

A             the amplitude of the sine wave

Since we are dealing with circular parts, the wavelength, l, is based on:

Where,

RPART       the radius of the part being measured

fUPR         the frequency of interest expressed in undulations per revolution (UPR)

which ultimately gives the sine wave radius on a circular part as:

What about Inside and Outside Diameters?

If we are measuring an outside diameter, we can use a larger tip radius to see all of the features of a given sine wave.  If we are measuring an inside diameter we will need a smaller radius in order to see the same features:  This figure shows a sine wave wrapped around a circle.  In doing so, the spacing between the peaks of the sine wave are effectively “widened” as compared to a sine wave on a straight reference line:

Ideally, we would like to combine the radius of curvature of the part with the radius of curvature of the sine wave.  Unfortunately, radius values do not mathematically combine, but curvature values do combine.  Mathematically, curvature is the inverse of the radius of curvature:

For an outside diameter, the largest allowable tip has a curvature of:

For an inside diameter, the curvatures add:

Thus for an Outside Diameter:

Outside diameter considerations:

Similarly, for an Inside Diameter:

Where:

A             the amplitude of the sine wave

RPART       the radius of the part being measured

fUPR         the frequency of interest expressed in undulations per revolution (UPR)

The above defined tip radius will actually touch the bottom of the sine wave, however it will only occur at a discrete point and will cause a “cusp” or “sharp corner”.

Since the cusp is very sharp, it will be filtered and some of the depth will be lost.  Thus, a smaller tip should be used in order to gain additional confidence.  A reduction of 25% may be adequate as a safety margin.

A 10 mm inside diameter has a roundness limit of 0.005 mm with a 50 UPR filter cutoff:

Using the inside diameter equation:

… and assuming that all of the peak-to-valley roundness error occurs at the highest frequency we have:

Inserting values:

Which gives a max tip radius of:

A 25% safety factor (multiply by 0.75) gives:

Conclusion

Roundness may continue to be debated.  But this discussion shows that the relationship between surface waveforms and the tip radius can be understood.

For more help understanding your toughest metrology challenges (and help with settling your debates) contact Digital Metrology today!

## Filtering for Roughness and Waviness

Check out this new animation!  This is based on some of Digital Metrology’s training materials and shows how the roughness and waviness profiles change with a changing filter cutoff.

The profile is from a milled surface with a 2.5 mm feed rate.

• The top left graph shows the primary & waviness profiles.
• The top right shows the wavelength content and the filter transmission curves
• The bottom graphs show roughness (left) and waviness (right)

Enjoy!

To find out more about your surfaces, or to schedule a training session contact Digital Metrology today!

## What’s with the “max”?

Many people have asked this question regarding roughness parameters.  Ramax? Rzmax?  These parameters often appear on drawings but don’t generally appear in measuring systems.

So let’s dig into this a bit.

First off “max” isn’t max

The extension “max” has nothing to do with a “maximum” or an upper limit.  The extension “max” is used to invoke what is called the “max rule”.  The “max-rule” deactivates the ISO default “16% rule”.  (More on this in a minute.)   In terms of specifics, when you put “max” at the end of a parameter name, you invoke the max rule and you are saying –

“no single trace on this surface is allowed to go outside this tolerance limit”.

For example, the “max” rule can be applied to upper and lower limits (based on ISO 1302 formatting):

The above example requires that all measurements of the “Ra” parameter lie between 0.2 (lower limit) and 0.6 (upper limit) micrometers.  Did you catch that last sentence where it said “measurements of the Ra parameter”?   “Ra” is the parameter that we report with our measuring system.  “max” is the rule that we use to judge the part as being good or bad.

Wait a minute!  I thought the limits are the limits…

ISO 4288 provides “decision rules” for using surface texture measurements in determining if a specific part is good or bad.  Buried in this standard is a default rule which says something to the effect of “unless otherwise specified; up to 16% of the traces on a surface are allowed yield results that are outside the tolerance”.

In other words, if you make 100 measurements on a specific surface on a specific piece of metal – you must treat the surface as “good” if less than 16 percent of the measurements are outside the tolerance limits.  Yes, that means you can get lots of “bad” readings, but the part must still be considered as “good”.

Yes… this would be a good part – even if all of the orange trace locations were outside the tolerance limits:

Why 16%?  Why not 17%?

The 16% come from statistics.  For a normally distributed set of results, the mean value, plus one standard deviation will include 84% of the observations.  Leaving 16% beyond the 1-sigma limit:

What to use?

For the most part, designers want to control all of the surface.  Thus they are inclined to think in terms of the “max” rule.  However, many surfaces have flaws or defects that might not be part of the actual “texture” produced by the manufacturing process.  These flaws or defects need to be controlled.  However, they may be controlled by other means… not necessarily surface texture.

For example, in the optics industry many specifications contain specific details regarding “scratches and digs”.  These “flaws” are described and controlled.  Thus, when measuring surface roughness, if a flaw is encountered in a specific trace, that specific trace does not have to fall inside the roughness tolerance limits.