Machine learning in production–potentials, challenges and exemplary applications

A Mayr, D Kißkalt, M Meiners, B Lutz, F Schäfer… - Procedia CIRP, 2019 - Elsevier
Recent trends like autonomous driving, natural language processing, service robotics or
Industry 4.0 are mainly based on the tremendous progress made in the field of machine …

Towards a smart electronics production using machine learning techniques

R Seidel, A Mayr, F Schäfer, D Kißkalt… - … spring seminar on …, 2019 - ieeexplore.ieee.org
High quality and low costs are main drivers in electronics production. Regardless of the
application, the trend towards batch size 1 heavily challenges current production systems …

Machine learning in electric motor production-potentials, challenges and exemplary applications

A Mayr, J Seefried, M Ziegler, M Masuch… - 2019 9th …, 2019 - ieeexplore.ieee.org
Artificial intelligence entails a wide range of technologies, which provide great potential for
tomorrow's electric motor production. Above all, data-driven techniques such as machine …

Quality Monitoring of Hairpin Joints Using Optical Coherence Tomography and Machine Learning

T Raffin, M Baader, M Masuch… - 2024 1st International …, 2024 - ieeexplore.ieee.org
Modern stators for electric traction drives rely on a technique known as hairpin winding,
which necessitates laser beam welding to join rectangular copper conductors. As stators …