Analytical modelling of in situ layer-wise defect detection in 3D-printed parts: additive manufacturing

• Published in: International journal of advanced manufacturing technology Vol. 111; no. 7-8; pp. 2311 - 2321
• Main Authors: Bowoto, Oluwole K., Oladapo, Bankole I., Zahedi, S. A., Omigbodun, Francis T., Emenuvwe, Omonigho P.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.12.2020; Springer Nature B.V
• Subjects: Additive manufacturing; Algorithms; CAE) and Design; Computer-Aided Engineering (CAD; Defects; Engineering; Fused deposition modeling; Industrial and Production Engineering; Literature reviews; Mechanical Engineering; Media Management; Original Article; Porosity; Printed materials; Three dimensional printing; Workpieces; Image processing; MATLAB; 3D printing; Real-time monitoring; Defect detection
• ISSN: 0268-3768; 1433-3015; 1433-3015
• DOI: 10.1007/s00170-020-06241-6

This study analyzes 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 3D object geometries 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 3D printer geometries, which solve material wastages by spotting defects during the workpieces layer-wise manufacturing process, thereby improving the economic advantages of additive manufacturing.