[HTML][HTML] Artificial Intelligence in manufacturing: State of the art, perspectives, and future directions

RX Gao, J Krüger, M Merklein, HC Möhring, J Váncza - CIRP Annals, 2024 - Elsevier
Inspired by the natural intelligence of humans and bio-evolution, Artificial Intelligence (AI)
has seen accelerated growth since the beginning of the 21st century. Successful AI …

[HTML][HTML] AI-based optimisation of total machining performance: A review

K Ullrich, M von Elling, K Gutzeit, M Dix… - CIRP Journal of …, 2024 - Elsevier
Advanced modelling and optimisation techniques have been widely used in recent years to
enable intelligent manufacturing and digitalisation of manufacturing processes. In this …

Safety-aware cascade controller tuning using constrained Bayesian optimization

M Khosravi, C König, M Maier, RS Smith… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
This article presents an automated, model-free, data-driven method for the safe tuning of PID
cascade controller gains based on Bayesian optimization. The optimization objective is …

Parameter identification of cutting forces in crankshaft grinding using artificial neural networks

I Pavlenko, M Saga, I Kuric, A Kotliar, Y Basova… - Materials, 2020 - mdpi.com
The intensifying of the manufacturing process and increasing the efficiency of production
planning of precise and non-rigid parts, mainly crankshafts, are the first-priority task in …

Performance-driven cascade controller tuning with Bayesian optimization

M Khosravi, VN Behrunani… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this article, we propose a performance-based autotuning method for cascade control
systems, where the parameters of a linear axis drive motion controller from two control loops …

Optimization for liquid cooling cylindrical battery thermal management system based on Gaussian process model

W Li, A Garg, M **ao, L Gao - Journal of …, 2021 - asmedigitalcollection.asme.org
The power of electric vehicles (EVs) comes from lithium-ion batteries (LIBs). LIBs are
sensitive to temperature. Too high and too low temperatures will affect the performance and …

Advances in artificial intelligence methods applications in industrial control systems: Towards cognitive self-optimizing manufacturing systems

E Carpanzano, D Knüttel - Applied Sciences, 2022 - mdpi.com
Industrial control systems play a central role in today's manufacturing systems. Ongoing
trends towards more flexibility and sustainability, while maintaining and improving …

Safe contextual Bayesian optimization integrated in industrial control for self-learning machines

S De Blasi, M Bahrami, E Engels… - Journal of Intelligent …, 2024 - Springer
Intelligent manufacturing applications and agent-based implementations are scientifically
investigated due to the enormous potential of industrial process optimization. The most …

[HTML][HTML] Autonomous and data-efficient optimization of turning processes using expert knowledge and transfer learning

M Maier, H Kunstmann, R Zwicker, A Rupenyan… - Journal of Materials …, 2022 - Elsevier
Process parameters in machining are predominantly selected by following manual tuning
procedures. Using data from the system and dedicated performance indicators combined …

Al-promp: Force-relevant skills learning and generalization method for robotic polishing

Y Wang, C Chen, F Peng, Z Zheng, Z Gao… - Robotics and Computer …, 2023 - Elsevier
Skill learning in robot polishing is gaining attention and becoming a hot issue. Current
studies on skill learning in robot polishing are mainly about trajectory skills, and force …