Deep reinforcement learning for self-tuning laser source of dissipative solitons
Increasing complexity of modern laser systems, mostly originated from the nonlinear
dynamics of radiation, makes control of their operation more and more challenging, calling …
dynamics of radiation, makes control of their operation more and more challenging, calling …
Structural decomposition-based energy consumption modeling of robot laser processing systems and energy-efficient analysis
Energy efficiency has been one of the main issues in manufacturing. Rapid energy
consumption (EC) calculation is the key to improving the efficiency of EC optimization. In this …
consumption (EC) calculation is the key to improving the efficiency of EC optimization. In this …
Visualizing laser ablation using plasma imaging and deep learning
High power laser ablation can lead to the creation of plasma and the emission of bright light,
which can prevent the direct observation of the workpiece. Alternative techniques for …
which can prevent the direct observation of the workpiece. Alternative techniques for …
Hybrid approach to synthesis of electromechanical block control system of mechatronic module
A Gorkavyy, M Gorkavyy, M Melnichenko… - AIP Conference …, 2023 - pubs.aip.org
One of the main elements of modern production automation are industrial robotic
manipulators, which can significantly increase labor productivity. However, together with the …
manipulators, which can significantly increase labor productivity. However, together with the …
Reinforcement Learning for Laser Welding Speed Control Minimizing Bead Width Error
T Kaneko, G Minamoto, Y Hirose… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
In this paper, we propose a method for reinforcement learning-based laser welding control.
Conventional methods apply standard reinforcement learning formulations to welding tasks …
Conventional methods apply standard reinforcement learning formulations to welding tasks …
Verifying the Applicability of Synthetic Image Generation for Object Detection in Industrial Quality Inspection
Sparse and imbalanced data is a common challenge that practitioners must overcome when
implementing industrial ML applications. This challenge concerns deep learning-based …
implementing industrial ML applications. This challenge concerns deep learning-based …
[CITATION][C] Machine Learning in Industrial Applications: Insights Gained from Selected Studies
M Schmitz - 2022 - Dissertation, Erlangen, Friedrich …