Improving metrology results with an adaptive measurement model – Metrology and Quality News

0

It is relatively easy to measure parts very close to tolerance. When the characteristics and tolerances to be measured are where you expect them, your measuring device can be programmed using the nominal form.

But early in a part’s life cycle, early in its design, and through the necessary iterations until the tool or mold and production parameters are perfected, this is often not the case.

This is common for 3D printed parts due to the complexity of the new process. This happens frequently with plastic injection molded parts because the mold is almost never right the first time, to name just 2 examples.

These same issues can occur with soft or soft parts, and parts that have already been used or are at the end of their life cycle, such as in the case of recoveries or simply by analyzing the behavior of parts over time. This happens even when measuring on simulation results which may be quite far from the nominal form.

It is much easier to measure such parts using dense data acquisition solutions such as computed tomography or optical scanners. With these technologies, the particular characteristic being measured is not taken into account alone, but the entire part is measured. This means that even though the GD&T features and tolerance zones that need to be qualified are still in the dataset, you may not know where exactly they are in space.

Today, these challenges are met – at least if you expect them – by one, using the scan of the deformed part itself to program the measurements, and hoping that the other parts will be deformed in a very similar way. This, however, results in almost complete reprogramming of the measurement routines involved, or at least a lot of manual rework in problem areas. A second option is to use local coordinate systems to reference areas that could be problematic with areas that will be stable and close enough to the problem. This can be done using datums or just individual coordinate systems, depending on the importance of the feature or the tolerance.

This procedure requires a lot of expertise and takes a bit more time and thought, but is considered state-of-the-art.

Both methods of dealing with warped part challenges – measuring on the scan itself or using many local coordinate systems and alignments – are expensive and time-consuming and labor-intensive. And you can still end up with measurement results that are not as stable and reliable as desired.

However, a new adaptive measurement model solves this fundamental metrology problem at the beginning or end of a life cycle, especially in the case of plastic injection molded parts or additive manufactured products.

While the historical method with unstable characteristics uses a single coordinate system (or even steps thereof), the adaptive measurement model creates an indefinite number of coordinates in space. Any measurement point can be assigned a motion, which points to the actual position as far as its corresponding measurement location actually is. Even if geometry is bent, moved, or scaled in one direction or axis, it can also be twisted and deformed by 6 degrees of freedom.

With this new model, thin sealing surfaces will be found as reliably as elements that have expanded beyond their size tolerance or exceeded the extent of the wall thickness.

The geometries are also not confused by elements belonging to another wall, i.e. where the normal looks correct, but the wall may actually belong to a different element.

The total coverage of the measurement points also improves greatly, because the search area is not restricted, as with the historical solutions, to a search vector or a search cone.

Search vectors will only provide partial measurement coverage in cases where the part is distorted, because at the furthest extent of the measurement point grid a few lines may fall through the air, where others can enter information on a territory that does not belong to the entity.

Summary:

The Adaptive Measurement Model is a truly novel method for minimizing measurement costs using dense data acquisition, allowing a manufacturer to employ a unique measurement methodology that can dramatically improve accuracy and ease of measurement. ‘use.

Benefits include:

Measure more accurately by identifying the best measurement points

Faster measurement by reducing measurement program complexity and using a single model

Take full advantage of the CAD model, especially when working with PMI data

Enable successful adoption of Industry 4.0 using a single numerical definition of a part’s tolerance requirements

For more information: www.volumegraphics.com

Author: Gerd Schwaderer, Metrology and CAD Product Manager, Volume Graphics GmbH

HOME PAGE LINK

Share.

Comments are closed.