Iso-scallop tool path planning for triangular mesh surfaces in multi-axis machining

Liang, Fusheng; Kang, Chris; Lu, Zhongyang

doi:10.1016/j.rcim.2021.102206

Cited by 23 publications

(4 citation statements)

References 47 publications

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“…A comparative test is proceeded to further elucidate the proposed method's benefits. Hereinto, two widely-used methods are introduced: (a) the end milling method with an iso-scallop height using ball-nosed cutters (Liang et al, 2021), and (b) the flank milling method with an iso-scallop height using drum-type cutters (Lu et al, 2022). For the two benchmarks, both u and v surface patch borders are used as the principal tool path.…”

Section: Comparison With the State-of-the-art Methodsmentioning

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: Comparison With the State-of-the-art Methodsmentioning

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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“…To realize the toolpath re-planning to smooth and desensitize the most sensitive axis, there are two problems to be solved, one is how to plan the CCP path to complete the material removal precisely and the other is how to plan the tool orientation to avoid collision and make the sensitive axis of the machine tool move smoother [12]. However, many more mature methods have been proposed from the perspective of CCP planning, and the planning method of reciprocal CCP path is already very reasonable for blade machining [13][14][15][16][17][18][19][20]. Therefore, this paper takes unchanging CCPs as the constraint and takes the desensitizing of the most sensitive axis as the target to replan the tool orientation.…”

Section: Introductionmentioning

confidence: 99%

Five-axis toolpath re-scheduling for facilitating assisted supporting thin-walled blade machining by decreasing axis sensitivity

Li,

Song,

et al. 2024

Int J Adv Manuf Technol

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Existing works in the optimization of five-axis machining mainly focus on the efficiency, precision, or dynamic performance of the machine tools, while the performance of other equipment which assists the machining process has not been considered. This paper takes the robot assisted supporting machining of thin-walled blades as the research objective, and proposes an axial-sensitivity-reduction based five-axis toolpath re-scheduling method for facilitating the collaborative support machining with a machine-tool and a robot. The input of the method is lenient, merely including the original toolpath and the workpiece point-cloud model. The output of the method is the re-scheduled toolpath which requires lower motion ability of the assisted support equipment. This is realized by the following approaches. First, an axial sensitivity concept is defined, which quantificationally reflects the influence extent of the machine-tool axis motion on the assisted supporter motion, thus the most sensitive axis which affects the assisted process maximally can be identified. Then, an optimal-partition dual-domain-assisted-fitting method is provided to reconstruct the parameterized geometrical model of blades according to the point-cloud model, thus the multi-value property of the blades which troubles the surface construction is solved. After that, a sensitive-axis-calming bidirectional-tangent-bug-searching method is proposed to re-schedule the toolpath of five-axis machining, thus reducing the sensitivity of the most-sensitive axis. The whole method is universal, because a general cutter model is used and the cutter-contact point keeps invariant after re-scheduling. The correctness and effectiveness of the proposed method are verified by illustration machining tests of a steam turbine blade using an AB-type five-axis machine tool.

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“…Tool path planning methods can be briefly classified into two categories: topological and parametric. Methods based on a topological form mainly include direction parallel methods [27,28], contour parallel methods [29][30][31][32][33], and space-filling curve methods [34][35][36][37][38]. Methods based on a parametric form mainly include iso-parametric methods [39,40], iso-plane methods [41,42], iso-scallop height methods [43][44][45][46], and vector field-based methods [47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

A framework from point clouds to workpieces

Shen

Wang

et al. 2022

Vis. Comput. Ind. Biomed. Art

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Combining computer-aided design and computer numerical control (CNC) with global technical connections have become interesting topics in the manufacturing industry. A framework was implemented that includes point clouds to workpieces and consists of a mesh generation from geometric data, optimal surface segmentation for CNC, and tool path planning with a certified scallop height. The latest methods were introduced into the mesh generation with implicit geometric regularization and total generalized variation. Once the mesh model was obtained, a fast and robust optimal surface segmentation method is provided by establishing a weighted graph and searching for the minimum spanning tree of the graph for extraordinary points. This method is easy to implement, and the number of segmented patches can be controlled while preserving the sharp features of the workpiece. Finally, a contour parallel tool-path with a confined scallop height is generated on each patch based on B-spline fitting. Experimental results show that the proposed framework is effective and robust.

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Iso-scallop tool path planning for triangular mesh surfaces in multi-axis machining

Cited by 23 publications

References 47 publications

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

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

Five-axis toolpath re-scheduling for facilitating assisted supporting thin-walled blade machining by decreasing axis sensitivity

A framework from point clouds to workpieces

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