Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Dominik Kißkalt"'
Publikováno v:
Sensors, Vol 22, Iss 3, p 811 (2022)
Convolutional neural network (CNN)-based approaches have recently led to major performance steps in visual recognition tasks. However, only a few industrial applications are described in the literature. In this paper, an object detection application
Externí odkaz:
https://doaj.org/article/3e46c89fcee24b84a63d241c804a7fe6
Publikováno v:
Procedia CIRP. 96:80-85
Industry 4.0 is associated with numerous technologies, which offer great potential for optimizing linear winding processes as used in electric motor manufacturing. To further increase flexibility and quality in the production of mass products like co
Publikováno v:
Procedia CIRP. 96:145-150
In product development, early decisions made within the requirements specification and design phase have significant impact on overall functionality, quality and lifecycle cost of the product. In Systems Engineering, these oftentimes iterative design
Publikováno v:
Journal of Intelligent Manufacturing. 32:1485-1495
In subtractive manufacturing, differences in machinability among batches of the same material can be observed. Ignoring these deviations can potentially reduce product quality and increase manufacturing costs. To consider the influence of the materia
Publikováno v:
Procedia CIRP. 93:1382-1387
A significant difference in the machinability of hard-to-machine materials can be observed among different batches of the same specified material. Thus, for cost-efficient machining, the ideal point of operation may vary for each batch. To investigat
Publikováno v:
Procedia CIRP. 93:401-406
Machine learning has often proven superior to traditional white-box modeling in industrial application scenarios. Yet the determinism in finding a solution close to the theoretical optimum is low due to human factors in the development process. Autom
Publikováno v:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
Publikováno v:
CASE
Microscopy is commonly used in machining to study the effects of tool wear. In modern tool condition monitoring systems, the analytical capabilities are further enhanced by machine learning, allowing for automated segmentation of the various visible
Publikováno v:
ICPS
In industrial manufacturing, a variety of different materials are used to manufacture goods in a cost-efficient manner. In situations where multiple materials are being used, such as compound parts, the machining becomes particularly challenging, as
Autor:
Tobias Gläßel, Johannes Seefried, Jörg Franke, Michael Weigelt, Benjamin Lutz, Dominik Kißkalt, Andreas Mayr
Publikováno v:
Zeitschrift für wirtschaftlichen Fabrikbetrieb. 114:145-149
Kurzfassung Industrie 4.0 geht mit einer Vielzahl an Technologien einher, die großes Potenzial für die Elektromotorenproduktion von morgen bieten. Vor allem datengetriebene Ansätze, die sich der Methoden des maschinellen Lernens (ML) bedienen, rü