Innovative strategies for addressing fatigue challenges in laser powder bed fusion of AlSi10Mg specimens and topologically optimised components

Abstract Surface roughness and process-induced defects, such as gas pores and lack of fusions, make additive manufacturing parts vulnerable to fatigue failure. As the conventional fatigue testing methods are time-consuming and require many specimens, several novel rapid fatigue test methods have emerged in recent years, including the stiffness method. In this work, the applicability of this method for AlSi10Mg parts printed by the laser powder bed fusion process is investigated. It is demonstrated that the stiffness method can obtain the fatigue limit of AlSi10Mg specimens with a small number of tests and has a minimal (1%) difference from conventional fatigue test method results. Furthermore, this methodology was applied to a fatigue demonstrator component obtained through a topology optimisation process. The fatigue limit of the demonstrator had less than a 10% difference compared to the conventionally tested ones and highlights the benefit of the stiffness method. In addition, these results led to the development of a framework which combines rapid fatigue testing and finite element modelling and can accurately predict the component fatigue life based on the results at the specimen scale, with a reported difference below 3%. This framework opens up a new avenue for faster qualification and certification of additively manufactured industrial components.

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Publication Details

Journal
Progress in Additive Manufacturing
Published
2025-08-18
DOI
https://doi.org/10.1007/s40964-025-01224-z
Citations
2
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
1.43
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article

Innovative strategies for addressing fatigue challenges in laser powder bed fusion of AlSi10Mg specimens and topologically optimised components

A. Mateo, Andrey Molotnikov, Sergi Parareda, Daniel Casellas et al.
2 citations
Progress in Additive Manufacturing
Additive Manufacturing Materials and Processes
1.43
article

Innovative strategies for addressing fatigue challenges in laser powder bed fusion of AlSi10Mg specimens and topologically optimised components

A. Mateo, Andrey Molotnikov, Sergi Parareda, Daniel Casellas, Raj Das, Milad Bemani Lirgeshas, Marc Mares Calvo
article en
2 citations

Abstract

Abstract Surface roughness and process-induced defects, such as gas pores and lack of fusions, make additive manufacturing parts vulnerable to fatigue failure. As the conventional fatigue testing methods are time-consuming and require many specimens, several novel rapid fatigue test methods have emerged in recent years, including the stiffness method. In this work, the applicability of this method for AlSi10Mg parts printed by the laser powder bed fusion process is investigated. It is demonstrated that the stiffness method can obtain the fatigue limit of AlSi10Mg specimens with a small number of tests and has a minimal (1%) difference from conventional fatigue test method results. Furthermore, this methodology was applied to a fatigue demonstrator component obtained through a topology optimisation process. The fatigue limit of the demonstrator had less than a 10% difference compared to the conventionally tested ones and highlights the benefit of the stiffness method. In addition, these results led to the development of a framework which combines rapid fatigue testing and finite element modelling and can accurately predict the component fatigue life based on the results at the specimen scale, with a reported difference below 3%. This framework opens up a new avenue for faster qualification and certification of additively manufactured industrial components.

Progress in Additive ManufacturingVol. 10(11)
Luleå University of Technology (SE), Fundació CTM Centre Tecnològic (ES), Forest Science and Technology Centre of Catalonia (ES), RMIT University (AU), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 18%
Additive Manufacturing Materials and Processes
1.43
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