AI MSE 2025
Lecture
18.11.2025 (CET)
A unique authenticator for additively manufactured parts derived from their microstructure
AW

Dr.-Ing. Anja Waske

Bundesanstalt für Materialforschung und -prüfung (BAM)

Gupta, K.¹; Poka, K.¹; Ulbricht, A.¹; Waske, A. (Speaker)²
¹Bundesanstalt für Materialforschung und -prüfung, Berlin; ²Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin
Vorschau
20 Min.

In the field of additive manufacturing, the ability to uniquely identify and authenticate parts is crucial for certification, logistics, and anti-counterfeiting efforts. This study introduces a novel methodology that leverages the intrinsic microstructural features of additively manufactured components for their identification, authentication, and traceability. Unlike traditional tagging methods, such as embedding QR codes on the surface [1] or within the volume of parts, this approach requires no alteration to the printing process, as it utilizes naturally occurring microstructural characteristics.

The proposed workflow [2] involves the analysis of 3D micro-computed tomography data to identify specific voids that meet predefined identification criteria. This method is demonstrated on a batch of 20 parts manufactured with identical process parameters, proving capable of achieving unambiguous identification and authentication. By establishing a tamper-proof link between the physical part and its digital counterpart, this methodology effectively bridges the physical and digital realms. This not only enhances the traceability of additively manufactured parts but also provides a robust tool for integrating digital materials, parts databases, and product passports with their physical counterparts.

References

[1] U. Jahnke, „Systematik zum präventiven Schutz vor Produktpiraterie durch AM“. Dissertation, Universität Paderborn, 2019.

[2] K. Gupta, K. Poka, A. Ulbricht, A. Waske; Identification and authentication of additively manufactured components using their microstructural fingerprint; Materials & Design; 2025; ISSN 0264-1275; https://doi.org/10.1016/j.matdes.2025.113986 .


Abstract

Abstract

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