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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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Hovedforfatter: Felica Tatzel, Leonie
Format: Online
Sprog:tysk
Udgivet: KIT Scientific Publishing 2022
Fag:
cut quality
convolutional neural network
machine learning
stainless steel
Laser cutting
Schnittqualität
Maschinelles Lernen
Edelstahl
Laserschneiden
Faltendes neuronales Netz
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
Online adgang:ONIX_20220218_9783731511281_17
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Summary: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.

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