Evaluation of Dimensional Accuracy in Additive Manufacturing with Complex Measurement Artifacts

Joch, Richard; Cedzo, Miroslav; Briliaková, Alžbeta; Mrázik, Jozef; Drbúl, Mário; Markovič, Jaromír

doi:10.2478/msr-2026-0005

Abstract

Accuracy and repeatability are among the key parameters in assessing the quality of additive manufacturing (AM) outputs, as they determine the usability of parts in technical and industrial practice. This study compares a standardized artifact defined by ISO/ASTM 52902 with a newly designed custom artifact, with measurements performed using a coordinate measuring machine (CMM) and 3D scanning. The dimensional deviations obtained for individual axes were statistically evaluated to determine whether the differences between artifacts and measurement methods were statistically significant. Additional analysis based on deviation mapping against the CAD model provided a more detailed view of process behavior for both simple and complex geometries. The results confirmed that the designed artifact can be considered a viable alternative to standardized solutions and offers advantages in practical applications, particularly in the context of quality control and optimization of measurement procedures.

References

Jadayel, M., Khameneifar, F. (2020). Improving geometric accuracy of 3D printed parts using 3D metrology feedback and mesh morphing. Journal of Manufacturing and Materials Processing, 4 (4), 112. https://doi.org/10.3390/jmmp4040112
Search in Google Scholar Back to article
Joch, R., Šajgalík, M., Drbúl, M., Holubják, J., Czán, A., Bechný, V., Matúš, M. (2023). The application of additive composites technologies for clamping and manipulation devices in the production process. Materials, 16 (10), 3624. https://doi.org/10.3390/ma16103624
Search in Google Scholar Back to article
Mohamed, O. A., Masood, S. H., Bhowmik, J. L. (2021). Modeling, analysis, and optimization of dimensional accuracy of FDM-fabricated parts using definitive screening design and deep learning feedforward artificial neural network. Advances in Manufacturing, 9, 115–129. https://doi.org/10.1007/s40436-020-00336-9
Search in Google Scholar Back to article
Grgić, I., Karakašić, M., Glavaš, H., Konjatić, P. (2023). Accuracy of FDM PLA polymer 3D printing technology based on tolerance fields. Processes, 11 (10), 2810. https://doi.org/10.3390/pr11102810
Search in Google Scholar Back to article
Beniak, J., Križan, P., Matúš, M., (2014). Accuracy of Rapid Prototyped models with using of FDM technology. Applied Mechanics and Materials, 613, 390–395. https://doi.org/10.4028/www.scientific.net/AMM.613.390
Search in Google Scholar Back to article
Scipioni, S. I., Lambiase, F. (2023). Error introduced by direct 3D printing of compression samples of PLA made by FDM process. The International Journal of Advanced Manufacturing Technology, 129, 4355–4368. https://doi.org/10.1007/s00170-023-12625-1
Search in Google Scholar Back to article
Beniak, J., Križan, P., Matus, M., Svatek, M. (2015). Ecological PLA plastic used for FDM rapid prototyping technology. In 15th International Multidisciplinary Scientific GeoConference (SGEM 2015). SGEM, 117–123. ISBN 978-1-5108-1002-0.
Search in Google Scholar Back to article
Ngo, T. D., Kashani, A., Imbalzano, G., Nguyen, K. T. Q., Hui, D. (2018). Additive manufacturing (3D printing): A review of materials, methods, applications and challenges. Composites Part B: Engineering, 143, 172–196. https://doi.org/10.1016/j.compositesb.2018.02.012
Search in Google Scholar Back to article
Wong, K. V., Hernandez, A. (2012). A review of additive manufacturing. International Scholarly Research Notices. https://doi.org/10.5402/2012/208760
Search in Google Scholar Back to article
Kaliamoorthy, P. S., Subbiah, R., Bensingh, J., Kader, A., Nayak, S. (2019). Benchmarking the complex geometric profiles, dimensional accuracy and surface analysis of printed parts. Rapid Prototyping Journal, 26 (2), 319–329. https://doi.org/10.1108/rpj-01-2019-0024
Search in Google Scholar Back to article
De Pastre, M.-A., Tagne, S.-C. T., Anwer, N. (2020). Test artefacts for additive manufacturing: A design methodology review. CIRP Journal of Manufacturing Science and Technology, 31, 14–24. https://doi.org/10.1016/j.cirpj.2020.09.008
Search in Google Scholar Back to article
Rebaioli, L., Fassi, I. (2017). A review on benchmark artifacts for evaluating the geometrical performance of additive manufacturing processes. The International Journal of Advanced Manufacturing Technology, 93, 2571–2598. https://doi.org/10.1007/s00170-017-0570-0
Search in Google Scholar Back to article
Moylan, S., Slotwinski, J., Cooke, A., Jurrens, K., Donmez, M. A. (2014). An additive manufacturing test artifact. Journal of Research of the National Institute of Standards and Technology, 119, 429–459. https://doi.org/10.6028/jres.119.017
Search in Google Scholar Back to article
Minetola, P., Iuliano, L., Marchiandi, G. (2016). Benchmarking of FDM machines through part quality using IT grades. Procedia CIRP, 41, 1027–1032. https://doi.org/10.1016/j.procir.2015.12.075
Search in Google Scholar Back to article
Vorkapić, N., Pjević, M., Popović, M., Slavković, N., Živanović, S. (2020). An additive manufacturing benchmark artifact and deviation measurement method. Journal of Mechanical Science and Technology, 34, 3015–3026. https://doi.org/10.1007/s12206-020-0633-2
Search in Google Scholar Back to article
Beniak, J., Holdy, M., Križan, P., Matúš, M. (2019). Research on parameters optimization for the Additive Manufacturing process. Transportation Research Procedia, 40, 144–149. https://doi.org/10.1016/j.trpro.2019.07.024
Search in Google Scholar Back to article
Joch, R., Šajgalík, M., Drbúl, M., Měřínská, D., Markovič, J., Czán, A. (2025). Impact of powder bed fusion printing process parameters on the achieved quality of PA12 manufactured parts. Progress in Additive Manufacturing, 10, 4123–4141. https://doi.org/10.1007/s40964-025-01053-0
Search in Google Scholar Back to article
Son, J., Choi, S. (2015). Orientation selection for printing 3D models. In 2015 International Conference on 3D Imaging (IC3D). IEEE. https://doi.org/10.1109/ic3d.2015.7391823
Search in Google Scholar Back to article
Adach, M., Sokołowski, P., Piwowarczyk, T., Nowak, K. (2021). Study on geometry, dimensional accuracy and structure of parts produced by multi jet fusion. Materials, 14 (16), 4510. https://doi.org/10.3390/ma14164510
Search in Google Scholar Back to article
Rivas Santos, V. M., Thompson, A., Sims-Waterhouse, D., Maskery, I., Woolliams, P., Leach, R. (2020). Design and characterisation of an additive manufacturing benchmarking artefact following a design-for-metrology approach. Additive Manufacturing, 32, 100964. https://doi.org/10.1016/j.addma.2019.100964
Search in Google Scholar Back to article
Stojkić, Ž., Culjak, E., Šaravanja, L. (2020). 3D measurement - comparison of CMM and 3D scanner. In 31st DAAAM International Symposium on Intelligent Manufacturing and Automation. DAAAM, 780–787. https://doi.org/10.2507/31st.daaam.proceedings.108
Search in Google Scholar Back to article
Cuesta, E., Meana, V., Álvarez, B. J., Giganto, S., Martínez-Pellitero, S. (2022). Metrology benchmarking of 3D scanning sensors using a ceramic GD&T-based artefact. Sensors, 22 (22), 8596. https://doi.org/10.3390/s22228596
Search in Google Scholar Back to article
Gapiński, B., Wieczorowski, M., Marciniak-Podsadna, L., Dybała, B., Ziółkowski, G. (2014). Comparison of different methods of measurement geometry using CMM, optical scanner and computed tomography 3D. Procedia Engineering, 69, 255–262. https://doi.org/10.1016/j.proeng.2014.02.230
Search in Google Scholar Back to article
Mendricky, R., Sobotka, J. (2020). Accuracy comparison of the optical 3D scanner and CT scanner. Manufacturing Technology, 20 (6), 791–801. https://doi.org/10.21062/mft.2020.120
Search in Google Scholar Back to article
Mohanavel, V., Kannan, S., Raman, M., Kulandaivel, A., Seikh, A. H., Iqbal, A. (2023). Impact of CNT addition on surface roughness and dimensional characteristics of polymer nano-composite fabricated by FDM method. The International Journal of Advanced Manufacturing Technology. https://doi.org/10.1007/s00170-023-12657-7
Search in Google Scholar Back to article
Filippidis, P., Papazetis, G., Vosniakos, G.-C. (2020). Process parameter investigation for 3D printing of cellular structured parts. Procedia Manufacturing, 51, 717–724. https://doi.org/10.1016/j.promfg.2020.10.101
Search in Google Scholar Back to article
Armillotta, A., Bellotti, M., Cavallaro, M. (2018). Warpage of FDM parts: Experimental tests and analytic model. Robotics and Computer-Integrated Manufacturing, 50, 140–152. https://doi.org/10.1016/j.rcim.2017.09.007
Search in Google Scholar Back to article
Kozior, T., Bochnia, J., Bochenek, A., Malara, D., Nawotka, M., Janša, J., Hajnyš, J., Wójtowicz, A., Měsíček, J. (2024). Estimating the uncertainty of measurements for various methods and 3D printed parts. Applied Sciences, 14 (8), 3506.
Search in Google Scholar Back to article

Evaluation of Dimensional Accuracy in Additive Manufacturing with Complex Measurement Artifacts

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