Year: 2025
Type: article
Abstract: Porosity characterization in metallic alloys is a fundamental aspect of materials engineering due to its influence on mechanical and structural properties. This study presents a method based on digital image processing for detecting and analyzing porosity in the AlSi10Mg aluminum alloy, additively manufactured using laser powder bed fusion (L-PBF). X-ray computed tomography, segmentation algorithms and filtering techniques were employed to identify and quantify the porosity present in the material’s microstructure. The research demonstrates that combining numerical methods with qualitative analysis provides a comprehensive understanding of porosity characteristics. Notably, the effectiveness of the proposed image processing methods was validated by comparing the results with actual material density measurements. However, challenges such as the need for proper calibration and potential imaging artifacts affecting accuracy were identified. This study represents a significant advancement in materials engineering, offering a detailed methodology for porosity analysis in aluminum alloys that not only enhances quality control and process optimization, but also improves segmentation accuracy and facilitates the reliable detection of small and interconnected pores in complex additively manufactured geometries.
DOI: 10.3390/jmmp9110374
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W4416266173