Merschroth, Holger ; Kniepkamp, Michael ; Weigold, Matthias
Hrsg.: Bourell, David L. ; Beaman, Joseph J. ; Crawford, Richard H. (2019)
Predicting and Controlling the Thermal Part History in Powder Bed Fusion Using Neutral Networks.
Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference. Austin, Texas (USA) (August 12-14, 2019)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Laser-based powder bed fusion of metallic parts is used widely in different branches of industry. Although there have been many investigations to improve the process stability, thermal history is rarely taken into account. The thermal history describes the parts' thermal situation throughout the build process as a result of successive heating and cooling with each layer. This could lead to different microstructures due to different thermal boundary conditions. In this paper, a methodology based on neural networks is developed to predict and control the parts' temperature by adjusting the laser power. A thermal imaging system is used to monitor the thermal history and to generate a training data set for the neural network. The trained network is then used to predict and control the parts temperature. Finally, tensile testing is conducted to investigate the influence of the adjusted process on the mechanical properties of the parts.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Herausgeber: | Bourell, David L. ; Beaman, Joseph J. ; Crawford, Richard H. |
| Autor(en): | Merschroth, Holger ; Kniepkamp, Michael ; Weigold, Matthias |
| Art des Eintrags: | Bibliographie |
| Titel: | Predicting and Controlling the Thermal Part History in Powder Bed Fusion Using Neutral Networks |
| Sprache: | Englisch |
| Publikationsjahr: | 12 August 2019 |
| Ort: | Austin, Texas (USA) |
| Verlag: | University of Texas |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Annual International Solid Freeform Fabrication Symposium — An Additive Manufacturing Conference |
| Buchtitel: | Proceedings of the 30th Annual International Solid Freeform Fabrication Symposium |
| Veranstaltungstitel: | Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference |
| Veranstaltungsort: | Austin, Texas (USA) |
| Veranstaltungsdatum: | August 12-14, 2019 |
| Kurzbeschreibung (Abstract): | Laser-based powder bed fusion of metallic parts is used widely in different branches of industry. Although there have been many investigations to improve the process stability, thermal history is rarely taken into account. The thermal history describes the parts' thermal situation throughout the build process as a result of successive heating and cooling with each layer. This could lead to different microstructures due to different thermal boundary conditions. In this paper, a methodology based on neural networks is developed to predict and control the parts' temperature by adjusting the laser power. A thermal imaging system is used to monitor the thermal history and to generate a training data set for the neural network. The trained network is then used to predict and control the parts temperature. Finally, tensile testing is conducted to investigate the influence of the adjusted process on the mechanical properties of the parts. |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > Additive Fertigung und Dentale Technologie (2021 aufgegangen in TEC Fertigungstechnologie) |
| Hinterlegungsdatum: | 02 Mär 2020 10:54 |
| Letzte Änderung: | 04 Mär 2020 14:53 |
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