A study comparing various density measurement methods of parts produced by additive manufacturing (AM) commissioned by Germany’s Fraunhofer IAPT has found that automated density determination developed by Dimensionics Density has advantages in certain areas.
Density determination of AM parts can be critical because of its impact on their structural integrity and performance, according to Dimensionics Density. It enables manufacturers to ensure part quality and reliability and helps identify defects, porosity, and voids within the material. Compared with three other density determination techniques, the method developed by Dimensionics Density is particularly recommended when density evaluation has to be made quickly or frequently, according to the Fraunhofer report. It also allows simplification of machine approvals, potentially reducing quality assurance costs.
Comparison of four density determination methods
In the report — “Analysis of measurement methods for density determination in additive manufacturing” — the use of micrographs, computed tomography, and the manual Archimedes method were evaluated in addition to automated density determination.
All of the methods are essentially capable of determining the relative density of AM parts, but the Fraunhofer IAPT report found that there are substantial differences in accuracy, resolution, repeatability, and the possibility of defect detection.
- Micrographs destroy the AM specimen. While they can provide partial insight into the actual condition of pores in a part, the process is characterized by a lot of manual work, adding time and cost and relying on a high degree of expertise, writes Dimensionics Density in the press release.
- Computed tomography (CT) also requires expertise. While it can provide a realistic 3D image of the internal porosity of a part, it is restricted in the pore size that it can detect. Moreover, CT equipment can be prohibitively expensive.
- The Archimedes method is the easiest to use but can be the least accurate, as the results can be affected by environmental conditions, the accuracy of the balance, as well as the precision of the experimental procedure. It is difficult to reproduce the results, which are strongly influenced by human factors, according to Dimensionics Density. Test specimens are never placed exactly the same on the balance, and the manual operation of the balances leads to measurement deviations.
How automated density determination works
Philipp Pruesse of Dimensionics Density described how the automated density determination process works. “Our process uses the Archimedes method mentioned above, but in combination with modern automation technology. The samples to be measured are placed in a special component carrier, which is provided with openings on the underside. These component carriers are transported through the system by an axis robot and, thus, lowered centrally and precisely onto the scales. On the scales themselves, a lift-out rack with pins is placed, which lifts the component over the openings in the component carrier, lifting it out of the carrier. The automated handling eliminates human influence on the measurement, as the parts are always placed identically onto the scales. The scales are designed to be insulated from vibration. In addition, all ambient conditions such as temperature, air pressure, and water temperature, are recorded via climate sensors, and their influence on the measurement result is taken into account directly in the evaluation algorithm when determining the density,” said Pruesse.
The only traceable method
The Fraunhofer IAPT benchmarking report notes that Dimensionics Density’s automated density determination removes the user from the Archimedean measurement and, therefore, has significantly higher repeatability and fewer fluctuations. The report also states that this method is the only one that is traceable, such that it can be referenced to a recognized standard via a measurement chain. Compared to micrographs and CT scans, the measurement time is also much shorter, making it easier to take multiple measurements for greater statistical confidence. This makes this method suitable for evaluating the process capability of machines, an essential step for the production of series components via AM.