Abstract

Additive manufacturing technologies enable various possibilities to create and modify the material composition and structure on a local level, but are often prone to undesired defects and inhomogeneities. This contribution makes use of such flaws to generate material-inherent, hidden codes and watermarks in metals for authentication and anti-counterfeiting applications. By controlled and random process variation, unique codes that can be read and authenticated by an eddy current device were produced with the processes of laser powder bed fusion (L-PBF) and laser directed energy deposition (L-DED). Two approaches are presented: First, volumetric, porous structures with a defined shape are manufactured with L-PBF. Second, coatings are fabricated by L-DED with alternating process parameters, leading to local deviations of the magnetic permeability. This non-deterministic coding approach generates a distinctive material structure that triggers high signal amplitudes in the eddy current measurement. Counterfeiting becomes impossible due to the irreproducible melt pool dynamics. Statistical hypothesis testing proves that the system is able to prevent false acceptance or rejection of a code with a certainty of 500 million to one. A low-cost setup for a novel locking system demonstrates that a code can be sensed reliably within one second.

Highlights

  • Additive manufacturing (AM) is characterized by a layer-wise generation of a part

  • With laser powder bed fusion (L-PBF), porous structures are fabricated with a reduced volume energy density

  • With laser directed energy deposition (L-DED), a varying melt pool depth and dilution of two materials with different magnetic permeability are generated by alternating process parameters

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Summary

Introduction

Additive manufacturing (AM) is characterized by a layer-wise generation of a part. Raw material such as powder or wire is processed to build a coherent volumetric structure, determining the material properties during buildup. Process-inherent deviations and imperfections can be turned into valuable features for special purposes: Since AM enables a local manipulation of the process, there are various possibilities to design the material composition and microstructure for a specific objective as shown by Loh et al [1], which is often referred to as tailored properties. Challenges arise from material science when multiple materials are combined as outlined by Tey et al [2] and Bandyopadhyay and Heer [3], as well as from production engineering, since the toolpath and process parameters need to be adapted locally as shown by Steuben et al [4]. Mitchell et al [5] forges the bridge to 4D printing of “smart” materials, which means that they respond in a predefined way to an external stimulus

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