Reinforcement learning for autonomous process control in industry 4.0: Advantages and challenges

N Nievas, A Pagès-Bernaus, F Bonada… - Applied Artificial …, 2024 - Taylor & Francis
In recent years, the integration of intelligent industrial process monitoring, quality prediction,
and predictive maintenance solutions has garnered significant attention, driven by rapid …

[HTML][HTML] A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability

S Pawanr, K Gupta - Energies, 2024 - mdpi.com
The pursuit of energy efficiency in machining processes is a critical aspect of sustainable
manufacturing. A significant portion of global energy consumption is by the industrial sector; …

Overcoming challenges: advancements in cutting techniques for high strength-toughness alloys in aero-engines

B Zhao, Y Wang, J Peng, X Wang, W Ding… - … Journal of Extreme …, 2024 - iopscience.iop.org
Aero-engines, the core of air travel, rely on advanced high strength-toughness alloys
(THSAs) such as titanium alloys, nickel-based superalloys, intermetallics, and ultra-high …

A digital twin defined autonomous milling process towards the online optimal control of milling deformation for thin-walled parts

C Zhang, G Zhou, Q Xu, Z Wei, C Han… - The International Journal of …, 2023 - Springer
Thin-walled parts are widely used in the aerospace industry, where the milling deformation
of the parts caused by their thin-walled dra** and extremely large size ratio characteristics …

Integrated carbon footprint with cutting parameters for production scheduling

B He, R Liu, T Li - Journal of Cleaner Production, 2023 - Elsevier
A large part of the global carbon footprint comes from manufacturing. Apart from material
distribution during product assembly, rational optimization of cutting parameters and …

Adaptive optimal process control with actor-critic design for energy-efficient batch machining subject to time-varying tool wear

Q **ao, Z Yang, Y Zhang, P Zheng - Journal of Manufacturing Systems, 2023 - Elsevier
Batch machining systems are essential for improving productivity and quality, but they
consume considerable amounts of energy due to the continuous interaction with machine …

[HTML][HTML] Machining parameter optimization for a batch milling system using multi-task deep reinforcement learning

P Wang, Y Cui, H Tao, X Xu, S Yang - Journal of Manufacturing Systems, 2025 - Elsevier
The integrated multi-objective optimization of machining parameters for improved machining
quality and efficiency is important in batch milling systems. Due to the change of the batch …

[HTML][HTML] Integrated optimisation of multi-pass cutting parameters and tool path with hierarchical reinforcement learning towards green manufacturing

F Lu, G Zhou, C Zhang, Y Liu, M Taisch - Robotics and Computer …, 2025 - Elsevier
Five-axis machining, especially flank milling, is popular in machining thin-walled freeform
surface parts with high energy consumption. Reducing the machining energy consumption …

Machining feature process route planning based on a graph convolutional neural network

Z Wang, S Zhang, H Zhang, Y Zhang, J Liang… - Advanced Engineering …, 2024 - Elsevier
The machining processes of machining features, as the crucial components of the
machining process for the overall part, significantly impact machining quality and production …

Towards energy efficient milling of variable curved geometries

SS Pawar, TC Bera, KS Sangwan - Journal of Manufacturing Processes, 2023 - Elsevier
Abstract Development of energy efficient machining is the present focus to industries for
reduction of energy consumption and making the manufacturing system more sustainable …