Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7205751 | Additive Manufacturing | 2018 | 14 Pages |
Abstract
In this study, we present the first results of a newly developed melt pool monitoring tool for selective laser melting, called DMP-meltpool. A manual data analysis method is given, and the events indicated by the analysis (DMP-meltpool events) are shown to correlate to the static tensile properties of the samples built. These events indicate the probability of material discontinuities (defects) in the metal additive manufacturing (AM) parts. In order to do so, cylindrical bars of Ti-6Al-4V ELI were built and monitored using DMP-meltpool. The tensile properties of the printed cylinders were correlated with the events detected by DMP-meltpool. An inverse relation between plastic elongation and the DMP-meltpool event density was observed. These results show that DMP-meltpool can be used to predict the quality of AM parts by detecting variations in the signals and tagging these events throughout the build as defects. Thus the technique can be employed for first stage in-line quality control of AM parts and for sorting out parts with potential defects non-destructively. The DMP-meltpool events could have significant correlations with other mechanical properties (like fatigue, hardness, fracture toughness, and crack propagation) since such properties are influenced by defects originating from the process instabilities.
Related Topics
Physical Sciences and Engineering
Engineering
Industrial and Manufacturing Engineering
Authors
Manisha Bisht, Nachiketa Ray, Frederik Verbist, Sam Coeck,