Analytical modelling of in-situ layer-wise defect detection in 3D Printed parts: Additive Manufacturing


This study analyses a software algorithm developed on MATLAB, which can be used to examine fused filament fabrication-based 3D printed materials for porosity and other defects that might affect the mechanical property of the final component under manufacture or the general aesthetic quality of a product. An in-depth literature review into the 3D printed materials reveals a rapidly increasing trend in its application in the industrial sector. Hence the quality of manufactured products cannot be compromised. Despite much research found to be done on this subject, there is still little or no work reported on porosity or defect detection in 3D printed components during (real-time) or after manufacturing operation. The algorithm developed in this study is tested for two different 3-D object geometry and the same filament color. The results showed that the algorithm effectively detected the presence or absence of defects in a 3D printed part geometry and filament colors. Hence, this technique can be generalized to a considerable range of 3-D printer geometries, which solve material wastages by spotting defects during the workpieces layer-wise manufacturing process, thereby improving the economic advantages of additive manufacturing.


The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.



Bowoto, O.K., Oladapo, B.I., Zahedi, S.A. et al. (2020) Analytical modelling of in situ layer-wise defect detection in 3D-printed parts: additive manufacturing. International Journal of Advanced Manufacturing Technology,


Research Institute

Institute of Engineering Sciences (IES)