Verbesserungen beim Laserschneiden mit Methoden des maschinellen Lernens

Verbesserungen beim Laserschneiden mit Methoden des maschinellen Lernens

Although laser cutting of metals is a well-established process, there is considerable potential for improvement with regard to various requirements for the manufacturing industry. First, this potential is identified and then it is shown how improvements could be made using machine learning. For this...

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Detalles Bibliográficos
Otros Autores: Felica Tatzel, Leonie (auth)
Formato: Libro electrónico
Idioma:Alemán
Publicado: Karlsruhe KIT Scientific Publishing 2022
Colección:Forschungsberichte aus der Industriellen Informationstechnik
Materias:
Electrical engineering
cut quality
convolutional neural network
machine learning
stainless steel
Laser cutting
Schnittqualität
Maschinelles Lernen
Edelstahl
Laserschneiden
Faltendes neuronales Netz
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654582606719
Descripción
Sumario:Although laser cutting of metals is a well-established process, there is considerable potential for improvement with regard to various requirements for the manufacturing industry. First, this potential is identified and then it is shown how improvements could be made using machine learning. For this purpose, a database was generated. It contains the process parameters, RGB images, 3D point clouds and various quality features of almost 4000 cut edges.
Descripción Física:1 electronic resource (234 p.)

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