AUTHOR=Nakhaei Mohsen , Sterba Manon , Foletti Jean-Marc , Badih Laurent , Behr Michel TITLE=Experimental analysis and numerical fatigue life prediction of 3D-Printed osteosynthesis plates JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2023.1133869 DOI=10.3389/fbioe.2023.1133869 ISSN=2296-4185 ABSTRACT=

The trend towards patient-specific medical orthopedic prostheses has led to an increased use of 3D-printed surgical implants made of Ti6Al4V. However, uncertainties arise due to varying printing parameters, particularly with regards to the fatigue limit. This necessitates time-consuming and costly experimental validation before they can be safely used on patients. To address this issue, this study aimed to employ a stress-life fatigue analysis approach coupled with a finite element (FE) simulation to estimate numerically the fatigue limit and location of failure for 3D-printed surgical osteosynthesis plates and to validate the results experimentally. However, predicting the fatigue life of 3D components is not a new concept and has previously been implemented in the medical device field, though without experimental validation. Then, an experimental fatigue test was conducted using a proposed modification to the staircase method introduced in ISO 12107. Additionally, a FE model was developed to estimate the stress cycles on the plate. The stress versus number of cycles to failure curve (S-N) obtained from the minimum mechanical properties of 3D-printed Ti6AI4V alloy according to ASTM F3001-14 to predict the fatigue limit. The comparison between experimental results and fatigue numerical predictions showed very good agreement. It was found that a linear elastic FE model was sufficient to estimate the fatigue limit, while an elastic-plastic model led to an accurate prediction throughout the implant’s cyclic life. The proposed method has great potential for enhancing patient-specific implant designs without the need for time-consuming and costly experimental regulatory testing.