Non-isometric dual-spline interpolation for five-axis machine tools by FIR filtering-based feedrate scheduling using pseudo curvature under axial drive constraint

Song, De-Ning; Zheng, De-Wei; Zhong, Yong; Ma, Jian-wei; Li, Jingsong

doi:10.1016/j.jmapro.2022.05.023

Cited by 6 publications

(1 citation statement)

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“…Therefore, it is pivotal to strike an optimal balance between cutting strip width, energy consumption and surface quality in the energy-efficient tool path optimisation. Additionally, since flank milling generates space movements of feeding and transmission systems (Song et al, 2022;Yoon et al, 2018), machining energy consumption tends to vary across principal paths along different feed angles. Unfortunately, there is a blank in the studies regarding the optimisation of feed angles to improve energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient tool path generation and expansion optimisation for five-axis flank milling with meta-reinforcement learning

Lu,

Zhou,

Zhang

et al. 2024

J Intell Manuf

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Five-axis flank milling is prevalent in complex surfaces manufacturing, and it typically consumes high electricity energy. To save energy and improve energy efficiency, this paper proposes a tool path optimisation of five-axis flank milling by meta-reinforcement learning. Firstly, considering flank milling features, a feed angle is defined that guides tool spatial motion and identifies an ideal principal path. Then, machining energy consumption and time are modelled by tool path variables, i.e., feed angle, cutting strip width and path length. Secondly, an energy-efficient tool path dynamic optimisation model is constructed, which is then described by multiple Markov Decision Processes (MDPs). Thirdly, meta-learning integrating with the Soft Actor-Critic (MSAC) framework is utilised to address the MDPs. In an MDP with one principal path randomly generated by a feed angle, cutting strip width is dynamically optimised under a maximum scallop height limit to realise energy-efficient multi-expansions. By quick traversal of MDPs with various feed angles, MSAC enables an energy-efficient path generation and expansion integrated scheme. Experiments show that, regarding machining energy consumption and time, the proposed method achieves a reduction of 69.96% and 68.44% over the end milling with an iso-scallop height, and of 41.50% and 39.80% over the flank milling with an iso-scallop height, with a minimum amount of machining carbon emission, which highlights its contribution to the arena of energy-oriented and sustainable intelligent manufacturing.

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Section: Introductionmentioning

confidence: 99%