A Pragmatic Approach for Rapid, Non-Destructive Assessment of Defect Types in Laser Powder Bed Fusion Based on Melt Pool Monitoring Data

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dc.date.accessioned2024-10-04T13:35:42Z
dc.date.available2024-10-04T13:35:42Z
dc.date.issued2024-07-03
dc.description.sponsorshipThis work was supported by the project DigiWerk funded within the research program “future” of the University of Kassel.eng
dc.identifierdoi:10.17170/kobra-2024100210908
dc.identifier.urihttp://hdl.handle.net/123456789/16081
dc.language.isoeng
dc.relation.doidoi:10.3390/ma17133287
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectadditive manufacturingeng
dc.subjectselective laser meltingeng
dc.subjectprocess monitoringeng
dc.subjectAlSi10Mgeng
dc.subjectMPMeng
dc.subject.ddc600
dc.subject.swdRapid Prototyping <Fertigung>ger
dc.subject.swdSelektives Laserschmelzenger
dc.subject.swdProzessüberwachungger
dc.subject.swdAluminiumlegierungger
dc.titleA Pragmatic Approach for Rapid, Non-Destructive Assessment of Defect Types in Laser Powder Bed Fusion Based on Melt Pool Monitoring Dataeng
dc.typeAufsatz
dc.type.versionpublishedVersion
dcterms.abstractProcess monitoring systems, e.g., systems based on photodiodes, could be used in laser-based powder bed fusion (PBF-LB/M) to measure various process parameters and process signatures to eventually allow for a local, detailed analysis of the produced parts. Here, simple statements only concerning the occurrence of defects in parts are sufficient in many cases, especially with respect to industrial application. Therefore, a pragmatic approach to rapidly infer the occurrence of defects and their types based on in situ data obtained by commercially available process monitoring systems is introduced. In this approach, a color distribution in form of a histogram is determined for each produced part using layer-wise screenshots of the visualized data provided by the monitoring software. Assessment of the histograms of AlSi10Mg samples, which were processed with different parameter combinations, revealed characteristics depending on the prevailing defect types. These characteristics enable the prediction of the occurring defect types without the necessity to apply conventional downstream testing methods, and thus, a straightforward separation of parts with good quality from defective components. Since the approach presented uses the data visualization of the monitoring software, it can be used even when direct access to the raw data is not provided by the machine manufacturer.eng
dcterms.accessRightsopen access
dcterms.creatorEngelhardt, Anna
dcterms.creatorWegener, Thomas
dcterms.creatorNiendorf, Thomas
dcterms.source.articlenumber3287
dcterms.source.identifiereissn:1996-1944
dcterms.source.issueIssue 13
dcterms.source.journalMaterialseng
dcterms.source.volumeVolume 17
kup.iskupfalse

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