PSI - Issue 34

Available online at www.sciencedirect.com Structural Integrity Procedia 00 (2019) 000 – 000 Available online at www.sciencedirect.com ScienceDirect

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Procedia Structural Integrity 34 (2021) 247–252

© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Esiam organisers are discussed and illustrated on an automotive use-case. © 2020 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Esiam organisers Keywords: Additive manufacturing; process simulation; fatigue; durability 1. Introduction Additive Manufacturing research has evolved greatly over the last years, from a prototyping tool to a mature technology suitable for structural applications. The challenge has now shifted from successfully printing a component, to accurately predicting its properties and performance. The unique characteristics of the additive process and the large array of relevant parameters (process settings such as laser power, speed and hatching pattern as well as design choices such as orientation within the build volume and post-treatments) all contribute to a large variability in material properties and part performance. BY-NC-ND license (h / c ecommo The second European Conference on the Structural Integrity of Additively Manufactured Materials The role of simulation in the industrialization of Additive Manufacturing N. Lammens a *, F. Gallego-Bordallo a , J. Ni a , A. Zinoviev a , T. De Weer a , H. Erdelyi a a Siemens Industry Software NV, Interleuvenlaan 68, 3001 Leuven, Belgium Abstract The nature of the Additive Manufacturing (AM) process leads to material properties that vary from point to point in the component. In order to properly design parts for structural (and mission-critical) applications, predictive simulation solutions are essential to industrializing AM. This paper presents a high-level overview of the current and on-going research activities to develop a process property-performance simulation chain allowing fatigue predictions accounting for the specific behavior of AM. Several aspects N. Lammens a *, F. Gallego-Bordallo a , J. Ni a , A. Zinoviev a , T. a

* Corresponding author. E-mail address: Nicolas.Lammens@siemens.com

2452-3216 © 2020 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Esiam organisers

2452-3216 © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Esiam organisers 10.1016/j.prostr.2021.12.035