Large-Scale Interlaboratory Study Along the Entire Process Chain of Laser Powder Bed Fusion: Bridging Variability, Standards, and Optimization across Metals and Polymers

Kuşoğlu IM, Garg S, Abel A, Balachandran PV, Barcikowski S, Becker L, Bernsmann JS, Boseila J, Broeckmann C, Coskun M, Dreyer M, East M, Easton M, Ellendt N, Gann S, Gökce B, Goßling M, Greiner J, Gruber P, Grünewald M, Gurung K, Hantke N, Hengsbach F, Holländer H, Van Hooreweder B, Hoyer KP, Huang Y, Huber F, Kessler O, Kısasöz BÖ, Kleszczynski S, Koc E, Kurzynowski T, Kwade A, Leupold S, Liu D, Lomo F, Lüddecke A, Luinstra GA, Mauchline DA, Meyer F, Meyer L, Middendorf P, Nolte S, Olejarczyk M, Overmeyer L, Pich A, Platt S, Radtke F, Ramm R, Rittinghaus SK, Rothfelder R, Rudloff J, Schaper M, Scheck ML, Schleifenbaum JH, Schmidt M, Sehrt JT, Shabanga YP, Sommereyns A, Steuer R, Tisha LS, Toenjes A, Tuck C, Vaghar A, Vrancken B, Wang Z, Weber S, Wegner J, Xu BX, Yang Y, Zhang D, Zhuravlev E, Ziefuss AR (2025)

Publication Type: Journal article

Publication year: 2025

Journal

DOI: 10.1002/adem.202402930

Abstract

Laser powder bed fusion is a cornerstone technology for additive manufacturing (AM) of metals and polymers, yet challenges in achieving consistent reproducibility and process optimization persist. Addressing these requires a systematic understanding of the interactions between feedstock, process parameters, and final part characteristics throughout the entire production chain. This study presents results from a comprehensive interlaboratory investigation conducted by 32 research institutions, evaluating six feedstock, including nanoparticle-modified aluminum alloy and polyamide powders, under standardized protocols. Data analysis encompasses 69 powder properties, 15 process parameters per print, and 78 part features, culminating in a dataset of over 1.2 million correlations. Advanced statistical methods and machine learning are employed to identify critical variability drivers, such as the impact of nanoparticle modifications on powder flowability and thermal conductivity, as well as the influence of process parameters on reproducibility. Newly introduced dimensionless figures of merit provide universal metrics to describe and predict thermal and mechanical interactions, simplifying process optimization and material characterization. The findings, supported by an open-access dataset adhering to findable, accessible, interoperable, and reusable principles, advance understanding of material–process–structure–property relationships. They establish a benchmark for future research and lay the foundation for improving the reliability, quality, and sustainability of AM processes.

Authors with CRIS profile

Involved external institutions

Laser Zentrum Hannover e.V. (LZH) Germany (DE) University of Virginia (UVA) United States (USA) (US) Universität Duisburg-Essen (UDE) Germany (DE) Ruhr-Universität Bochum (RUB) Germany (DE) Universität Stuttgart Germany (DE) Friedrich-Schiller-Universität Jena Germany (DE) Wrocław University of Science and Technology / Politechnika Wrocławska Poland (PL) Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen Germany (DE) Gottfried Wilhelm Leibniz Universität Hannover Germany (DE) Fatih Sultan Mehmet Vakif University / Fatih Sultan Mehmet Vakıf Üniversitesi Turkey (TR) Universität Paderborn Germany (DE) Fraunhofer-Institut für Angewandte Optik und Feinmechanik (IOF) / Fraunhofer Institute for Applied Optics and Precision Engineering Germany (DE) University of Nottingham United Kingdom (GB) RMIT University Australia (AU) Leibniz-Institut für Werkstofforientierte Technologien (IWT) Germany (DE) SKZ - KFE gGmbH Germany (DE) Bergische Universität Wuppertal Germany (DE) Vaal Univerrsity of Technology South Africa (ZA) Universität Rostock Germany (DE) Katholieke Universiteit Leuven (KUL) / Catholic University of Leuven Belgium (BE) Sichuan University (SCU) / 四川大学 China (CN) Technische Universität Braunschweig Germany (DE) Universität Hamburg (UHH) Germany (DE) Technische Universität Darmstadt Germany (DE)

How to cite

APA:

Kuşoğlu, I.M., Garg, S., Abel, A., Balachandran, P.V., Barcikowski, S., Becker, L.,... Ziefuss, A.R. (2025). Large-Scale Interlaboratory Study Along the Entire Process Chain of Laser Powder Bed Fusion: Bridging Variability, Standards, and Optimization across Metals and Polymers. Advanced Engineering Materials. https://doi.org/10.1002/adem.202402930

MLA:

Kuşoğlu, Ihsan Murat, et al. "Large-Scale Interlaboratory Study Along the Entire Process Chain of Laser Powder Bed Fusion: Bridging Variability, Standards, and Optimization across Metals and Polymers." Advanced Engineering Materials (2025).

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