AI MSE 2025
Lecture
19.11.2025 (CET)
A Digital Object Identifier for Additively Manufactured Parts as Software Project
HQ

Heike Quosdorf (M.Sc.)

Bundesanstalt für Materialforschung und -prüfung (BAM)

Quosdorf, H. (Speaker)¹; Ferlemann, K.²; Habdank, M.²; Jahnke, U.²; Waske, A.¹
¹Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin; ²Additive Marking GmbH, Paderborn
Vorschau
20 Min.

A method to uniquely identify samples [1] without printed or handwritten labels is an advantage not just for additively manufactured parts. To kickstart industry use cases it is also important to provide a ready-made implementation kit. Following an open-science and open-source software approach Germanys Federal Institute for Materials Research and Testing (BAM) seeks to promote digital solutions of ongoing research projects. With this software package a novel method based on microstructural features as identifiers – DOI4AM (digital object identifier for additively manufactured parts) – will be explained alongside its implementation as Python software package.

The digital object identifier (DOI) links product data clearly and forgery-proof with real components. Its implementation helps to identify and securely authenticate additively manufactured components during its product life cycle by using characteristic microstructure features - just like a fingerprint. To calculate the DOI fingerprint, a few preprocessing steps need to be performed to detect the uniquely distributed microstructure features that occur during the 3D printing process. A go-through guide shows the preprocessing steps that include CT image capturing, feature segmentation and data distribution with CSV files. While all steps can be followed along in a Jupyter notebook, the software package includes an application for creating and checking of previously created fingerprints, as well, as a containerized API (application programming interface) service for implementation in existing software platforms or workflows. While data visualization is crucial to understand the methodology and an essential tool to check for data correctness, an implementation in an industry use case needs to be slim and resource efficient. Therefor the software’s API can be used as an independent service. The projects industry partner proofs its first successful implementation in their digital product passport web solution PASS-X [2].

[1] Kanhaiya Gupta, Konstantin Poka, Alexander Ulbricht, Anja 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.

[2] Additive Marking; Vertreten durch die Geschäftsführer: Dr.-Ing. Ulrich Jahnke, Dr.-Ing. Matthias Habdank; Handelsregister: Amtsgericht Paderborn, HRB 13636; https://pass-x.eu/de


Abstract

Abstract

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