TY - JOUR A1 - Franz, Daniel A1 - Yang, Yongting A1 - Esen, Cemal A1 - Hellmann, Ralf ED - Esen, Cemal T1 - Flexible 2D Laser Cutting of Ultra-Thin Glass Using an Ultrashort Pulsed Laser Robotic System JF - Journal of Laser Micro/Nanoengineering KW - Laserschneiden KW - Ultrakurzzeitlaser Y1 - 2026 U6 - https://doi.org/10.2961/jlmn.2026.01.2004 SN - 1880-0688 VL - 21 IS - 1 PB - Japan Laser Processing Society ER - TY - JOUR A1 - Schleier, Max A1 - Esen, Cemal A1 - Hellmann, Ralf T1 - Vision transformer based cut interruption detection and prediction of laser fusion cutting from monitored melt pool images JF - Journal of Laser Applications N2 - Incomplete cuts during laser fusion cutting result in a closed kerf, preventing the workpiece from detaching from the sheet and resulting in rework or rejection. We demonstrate the approach of a vision transformer, used for image classification, to detect cut interruption during laser fusion cutting in steel and aluminum. With events impending an incomplete cut in steel, we attempt to predict cut interruption before they even occur. To build a data set for training, cutting experiments are carried out with a 4 kW fiber laser, forcing incomplete cuts by varying the process parameters such as laser power and feed rate. The thermal radiation from the process zone during the cutting process is captured with a size of 256 × 256 px2 at sample rates of 20 × 103 fps. The kerf is recorded with a spectral sensitivity between 400 and 700 nm, without external illumination, which enables the melt to be observed in the range of the visual spectrum. The vision transformer model, which is used for image classification, splits the image into patches, linearly embedded with an added position embedding, and fed to a standard transformer encoder. For training the model, a set of images was labeled for the respective classes of a complete, incomplete, and impending incomplete cut. With the trained model, incomplete cuts in steel and aluminum can then be recognized and impending incomplete cuts in steel can be predicted in advance. KW - Laserschneiden KW - Laserschmelzen Y1 - 2025 U6 - https://doi.org/10.2351/7.0001611 SN - 1042-346X VL - 37 IS - 1 PB - Laser Institute of America ER - TY - JOUR A1 - Schleier, Max A1 - Esen, Cemal A1 - Hellmann, Ralf T1 - Evaluation of a Cut Interruption Algorithm for Laser Cutting Steel and Aluminum with a High-Speed Camera JF - Applied Sciences N2 - We report on a monitoring system based on a high-speed camera for fiber laser fusion cutting. The monitoring system is used without an external illumination retrofit on a conventional cutting head, with the optical path aligned coaxially to the incident laser, permitting a direct, spatially, and temporally resolved detection of the melt pool area in the cut kerf from the top view. The dependence of the melt pool area on laser processing parameters such as laser power and feed rate are thus evaluated for stainless steel, zinc-coated steel, and aluminum, respectively. The signal characteristics of the images captured from the melt pool are examined in the visible spectral range of the emitted secondary thermal radiation from the process zone. An ad hoc developed image processing algorithm analyzes the spectral and geometric information of the melt pool from high-speed camera images and distinguishes between complete and incomplete cuts. KW - Laserschneiden KW - Laserschmelzen Y1 - 2023 U6 - https://doi.org/10.3390/app13074557 SN - 2076-3417 VL - 13 IS - 7 PB - MDPI AG ER -