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This document describes various image processing techniques to be used for defect characterization of additively manufactured parts. This will help the reader gain knowledge of materials science engineering and the nuances in analyzing data from image processing software.
Additive manufacturing is shaping the manufacturing world through simplistic household printers’ to more complex metal printers used for a variety of applications. Specifically, laser powder bed fusion (LPBF) is an additive manufacturing process that deposits metal powder over the build plate and melts it with a laser in the shape of the build part. In order to make LPBF more efficient with higher quality material, an experiment was done using in-situ monitoring sensors to observe the LPBF process as it prints the nickel super-alloy 718. The focus of this experiment was to observe defects in the printing process such as pores and inclusions. The LPBF machine printed two separate parts, one small coupon and one larger coupon. Changing the geometry for LPBF parts will create different outcomes microscopically, because of the different thermal histories, that result in different defect characteristics. Using image processing techniques, the defects can be characterized to help understand the relationship between geometry and porosity. The implications of this research highlight the impact to the structural integrity of printed LPBF parts, which will help ensure that future materials have less defects, are stronger, and have a higher level of quality.
Engineering | Materials Science and Engineering | Metallurgy
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Engineering and Computer Science
Mechanical and Materials Engineering
D'Alesandro , S., Gockel , J., & Harvey , A. (2020). Defect Characterization of Additively Manufactured Parts. .
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