This paper proposes a deep reinforcement learning (DRL) method to drive an optimal multi-pass energy-efficient parametric scheme for aviation parts in flank ...

Nov 26, 2022 · To address the issue, this paper proposes a novel multi-pass parametric optimisation based on deep reinforcement learning (DRL), allowing ...

Feb 6, 2023 · To address the issue, this paper proposes a novel multi-pass parametric optimisation based on deep reinforcement learning (DRL), allowing ...

As the main processing method for aviation parts, flank milling usually adopts multi-pass constant and conservative cutting parameters to prevent workpiece ...

Nov 18, 2022 · This paper proposes a deep reinforcement learning (DRL) method to drive an optimal multi-pass energy-efficient parametric scheme for aviation ...

Optimisation objectives. To improve energy efficiency for flank milling of thin-walled and freeform surface parts, machining time ...

Cutting parameters play a major role in improving the energy efficiency of the manufacturing industry. As the main processing method for aviation parts, flank ...

Lu, Energy-efficient multi-pass cutting parameters optimisation for aviation parts in flank milling with deep reinforcement learning, Robot. Cim.-Int. Manuf ...

Jun 7, 2024 · To save energy and improve energy efficiency, this paper proposes a tool path optimisation of five-axis flank milling by meta-reinforcement ...

Cutting parameters play a major role in improving the energy efficiency of the manufacturing industry. As the main processing method for aviation parts, flank ...