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Proposes Geometric Accuracy and Surface Roughness Estimation of Anatomical Models of the Pelvic Area Manufactured Using a Material Extrusion Additive Technique

Authors :
Paweł Turek
Sławomir Snela
Grzegorz Budzik
Anna Bazan
Jarosław Jabłoński
Łukasz Przeszłowski
Robert Wojnarowski
Tomasz Dziubek
Jana Petru
Source :
Applied Sciences, Vol 15, Iss 1, p 134 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

One of the main benefits of using 3D printing in orthopedics is the ability to create custom solutions tailored to a patient’s specific anatomical and functional needs. Conducting a reliable evaluation of the accuracy of the manufacture of anatomical structure models is essential. However, particular standards or procedures still need to be implemented to control the surface quality of anatomical models manufactured using additive manufacturing techniques. Models of pelvic parts made of polylactic acid (PLA) material were manufactured using the Material Extrusion (MEX) additive technique. Subsequently, guidelines were developed to reliably verify the geometric and surface roughness of the 3D printed models using Computer-Aided Inspection (CAI) systems. For this purpose, a measuring arm system (MCA-II) with a mounted laser head and Atos II Triple Scan was used. To inspect surface roughness parameters, procedures were developed for an Alicona InfiniteFocusG4 optical microscope. The results of the geometrical verification of the models are within the tolerance limits of ±0.22 mm to ±0.6 mm. In the case of surface roughness measurement, the highest values for the arithmetical mean height Sa were obtained on the side of the support material, while the smallest values were found along the applied layers. After the metrological control process, the models were used in the planning process for hip surgery.

Details

Language :
English
ISSN :
20763417
Volume :
15
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.8bb21c3ba39d4a53860dd1fb2cfd98e1
Document Type :
article
Full Text :
https://doi.org/10.3390/app15010134