International Journal of Automation Technology

Journal: International Journal of Automation Technology

Abbreviation

Int. J. Automation Technol

Publisher

Fuji Technology Press

ISSN

1883-8022
1881-7629

Show all metadata

Search Results

Publications 1 - 10 of 16

Orientation smoothing for 5-axis machining using quasi-redundant degrees of freedom
Sellmann, Florian; Haas, Titus; Nguyen, Hop D.; et al. (2016)
International Journal of Automation Technology
Increased productivity for redundant laser scanners using an optimal trajectory separation method
Haas, Titus; Warhanek, Maximilian; Dietlicher, Michael; et al. (2016)
International Journal of Automation Technology
MPCC-based set point optimisation for machine tools
Haas, Titus; Weikert, Sascha; Wegener, Konrad (2019)
International Journal of Automation Technology
Influence of the Anode Material and the Flushing Gas on the Dry Electrical Discharge Machining Process
Roth, Raoul; Beck, Lukas; Balzer, Hartmi; et al. (2013)
International Journal of Automation Technology
Special Issue on Advanced Material Driven Design of Machine Tools
Wegener, Konrad; Matsubara, Atsushi (2020)
International Journal of Automation Technology
Machine Tool Energy Efficiency – A Component Mapping-Based Approach
Schudeleit, Timo; Züst, Simon; Weiss, Lukas; et al. (2016)
International Journal of Automation Technology
Geometry optimisation for 2D cutting: A quadratic programming approach
Sellmann, Florian; Haas, Titus; Nguyen, Hop D.; et al. (2016)
International Journal of Automation Technology
Automatic Characterization of WEDM Single Craters Through AI Based Object Detection
Gonzalez Sanchez, Eduardo; Saccardo, Davide; Borges Esteves, Paulo; et al. (2024)
International Journal of Automation Technology
Wire electrical discharge machining (WEDM) is a process that removes material from conductive workpieces by using sequential electrical discharges. The morphology of the craters formed by these discharges is in-fluenced by various process parameters and affects the quality and efficiency of the machining. To understand and optimize the WEDM process, it is essential to iden-tify and characterize single craters from microscopy images. However, manual labeling of craters is tedious and prone to errors. This paper presents a novel approach to detect and segment single craters using state-of-the-art computer vision techniques. The YOLOv8 model, a convolutional neural network-based object detection technique, is fine-tuned on a custom dataset of WEDM craters to locate and enclose them with tight bounding boxes. The segment anything model, a vision transformer-based instance segmentation technique, is applied to the cropped images of individual craters to delineate their shape and size. Geometric analysis of the segmented craters reveals significant variations in their contour and area depending on the energy set-ting, while the wire diameter has minimal influence.
Towards Decentralized Production: A Novel Method to Identify Flexibility Potentials in Production Sequences Based on Flexibility Graphs
Bochmann, Lennart; Gehrke, Lars; Böckenkamp, Adrian; et al. (2015)
International Journal of Automation Technology
Thermally Caused Location Errors of Rotary Axes of 5-Axis Machine Tools
Gebhardt, Michael; Schneeberger, Alexander; Weikert, Sascha; et al. (2014)
International Journal of Automation Technology

Publications 1 - 10 of 16

Journal: International Journal of Automation Technology

Abbreviation

Publisher

Journal Volumes

ISSN

Description

Filters

Search Results