Machine Learning Approach for Optimization of Automated Fiber Placement Processes

Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review

Autoren

  • J. Brüning
  • B. Denkena
  • M. A. Dittrich
  • T. Hocke

Organisationseinheiten

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Details

OriginalspracheEnglisch
Seiten (von - bis)74-78
Seitenumfang5
FachzeitschriftProcedia CIRP
Jahrgang66
PublikationsstatusVeröffentlicht - 6 Juni 2017
Veranstaltung1st CIRP Conference on Composite Materials Parts Manufacturing, CIRP CCMPM 2017 - Karlsruhe, Deutschland
Dauer: 8 Juni 2017 → 9 Juni 2017

Abstract

Automated Fiber Placement (AFP) processes are commonly deployed in manufacturing of lightweight structures made of carbon fibre reinforced polymer. In general, AFP is connected to individual manufacturing knowledge during process planning and time consuming manual quality inspections. In both cases, automatic solutions provide a high economic potential. Therefore, a machine learning approach for planning, optimizing and inspection of AFP processes is presented. Process data from planning, CNC and online process monitoring is aggregated for the documentation of the part specific manufacturing history and the automated generation of manufacturing knowledge. Within this approach a complete automation of data capturing, data storing, modeling and optimizing is achieved.

ASJC Scopus Sachgebiete

Zitieren

Machine Learning Approach for Optimization of Automated Fiber Placement Processes. / Brüning, J.; Denkena, B.; Dittrich, M. A. et al.
in: Procedia CIRP, Jahrgang 66, 06.06.2017, S. 74-78.

Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review

Brüning, J, Denkena, B, Dittrich, MA & Hocke, T 2017, 'Machine Learning Approach for Optimization of Automated Fiber Placement Processes', Procedia CIRP, Jg. 66, S. 74-78. https://doi.org/10.1016/j.procir.2017.03.295
Brüning, J., Denkena, B., Dittrich, M. A., & Hocke, T. (2017). Machine Learning Approach for Optimization of Automated Fiber Placement Processes. Procedia CIRP, 66, 74-78. https://doi.org/10.1016/j.procir.2017.03.295
Brüning J, Denkena B, Dittrich MA, Hocke T. Machine Learning Approach for Optimization of Automated Fiber Placement Processes. Procedia CIRP. 2017 Jun 6;66:74-78. doi: 10.1016/j.procir.2017.03.295
Brüning, J. ; Denkena, B. ; Dittrich, M. A. et al. / Machine Learning Approach for Optimization of Automated Fiber Placement Processes. in: Procedia CIRP. 2017 ; Jahrgang 66. S. 74-78.
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AU - Brüning, J.

AU - Denkena, B.

AU - Dittrich, M. A.

AU - Hocke, T.

PY - 2017/6/6

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