## 5 Discussion  
Repeatability and reproducibility have been on the rise in additive manufacturing recently. They depend on the type of technology, production and post-processing, 3D printers and materials [41]. Authors [PERSON] et al. [41] in their paper on metal additive production concluded that the level of complexity and interconnectedness between parameters (powder morphology, laser characteristics and scan pattern) leads to an improvement of the repeatability and reproducibility of additive manufacturing processes. Our results indicate that state-of-the-art CT metrology can be recommended as a method of choice for the inspection of polymer AM parts, as achievable accuracy is more than adequate for these components, while measurement time can be kept relatively short (less than 8 min). This coincides with the results of authors [PERSON] et al. who also found that CT scanning is a great method that enables a detailed view of 3D printed parts [42]. Authors [PERSON] et al. tried to establish a comparison in the repeatability of the results in additive manufacturing test plates with CT analysis and coordinate measuring machine (CMM) and their results also support our findings [18]. They concluded that CT is suitable for verification and acceptance of AM parts, conformity and correlation between measurements, visual comparison and deviation of overlap scanned CT data to original CAD models of a variety of AM methods, which provided a means to preliminary analyse the form that is created as well as its differences in feature position [18]. Results of the deviations in the \(x\) axis were in the range from \(-8\)\(\upmu\)m to \(76\)\(\upmu\)m, and for the \(y\) axis, in the range from \(-10\)\(\upmu\)m to \(100\)\(\upmu\)m. Deviations in the \(z\) axis were grouped around \(100\)\(\upmu\)m, ranging from \(56\)\(\upmu\)m to \(197\)\(\upmu\)m, while cylindricity error ranged from \(0.25\) mm to \(0.50\) mm. In comparison to other test plates, the first three groups (No. 1.x; 2.x and 3.x were \(x=1\), 2, 3) showed higher values of deviations in the \(x\) and \(y\) position, as well as in the conicity error. As was the case with the accuracy, achieved repeatability for measurands (distance) in the \(x\) and \(y\) axis was better than it was for the \(z\) axis (which is also inferred from the mechanical properties in the reference [24]). For seven sets of test plates average value of measurement ranges in the \(x\) axis was \(26\)\(\upmu\)m, and \(25\)\(\upmu\)m in the \(y\) axis. For the \(z\) axis, average value of measurement ranges was \(49\)\(\upmu\)m.  
Volumetric measurement results, for which examples of histograms are given in Figures 11 and 12, indicate that 95% of deviations from nominal values (errors in manufacturing of test plates) are contained within the range of \(\pm 100\)\(\upmu\)m. For the majority of plates that were printed during this study, the deviations were distributed according to Gauss distribution; 19 analysed test plates (as shown in Figure 12) showed normal distribution of deviations from nominal CAD data, and for three plates (No. 1.2; 2.3; 3.1), binominal distributions were observed (as shown in Figure 13). While Gaussian  
Figure 13: Volumetric deviation from CAD model on test plate No. 3.1. A bimodal distribution can be seen, suggesting that a systematic error source was present during manufacturing. distribution indicates that only random errors occur in the manufacturing process, without systematic errors, it is difficult to draw conclusions about underlying causes of binomial deviation distributions; this effect could be attributed to a systematic error in the manufacturing process, but since the majority of samples did not show this effect, other possible causes shall be investigated in further research. Regardless, the ranges of deviations given above can be used as an expectation of the achievable accuracy of PolyJet technology-based printers when printing rather small parts.