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Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion

Harbig, Jana ; Wenzler, David L. ; Baehr, Siegfried ; Kick, Michael K. ; Merschroth, Holger ; Wimmer, Andreas ; Weigold, Matthias ; Zaeh, Michael F. (2022):
Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion. (Publisher's Version)
In: Materials, 15 (3), MDPI, e-ISSN 1996-1944,
DOI: 10.26083/tuprints-00021022,
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Item Type: Article
Origin: Secondary publication DeepGreen
Status: Publisher's Version
Title: Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion
Language: English
Abstract:

Additive manufacturing, in particular the powder bed fusion of metals using a laser beam, has a wide range of possible technical applications. Especially for safety-critical applications, a quality assurance of the components is indispensable. However, time-consuming and costly quality assurance measures, such as computer tomography, represent a barrier for further industrial spreading. For this reason, alternative methods for process anomaly detection using process monitoring systems have been developed. However, the defect detection quality of current methods is limited, as single monitoring systems only detect specific process anomalies. Therefore, a new methodology to evaluate the data of multiple monitoring systems is derived using sensor data fusion. Focus was placed on the causes and the appearance of defects in different monitoring systems (photodiodes, on- and off-axis high-speed cameras, and thermography). Based on this, indicators representing characteristics of the process were developed to reduce the data. Finally, deterministic models for the data fusion within a monitoring system and between the monitoring systems were developed. The result was a defect detection of up to 92% of the melt track defects. The methodology was thus able to determine process anomalies and to evaluate the suitability of a specific process monitoring system for the defect detection.

Journal or Publication Title: Materials
Volume of the journal: 15
Issue Number: 3
Place of Publication: Darmstadt
Publisher: MDPI
Collation: 13 Seiten
Uncontrolled Keywords: additive manufacturing, multi-monitoring, PBF-LB/M, spatter
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW)
Date Deposited: 11 Apr 2022 11:21
Last Modified: 27 Oct 2022 05:45
DOI: 10.26083/tuprints-00021022
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-210225
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21022
PPN: 500770255
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