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    A Deformation Control Method in Thin-Walled Parts Machining Based on Force and Stiffness Matching Via Cutter Orientation Optimization

    Source: Journal of Manufacturing Science and Engineering:;2022:;volume( 145 ):;issue: 003::page 31007-1
    Author:
    Cai, Yonglin
    ,
    Zhang, Zhengzhong
    ,
    Xi, Xiaolin
    ,
    Zhao, Defu
    DOI: 10.1115/1.4056073
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In the milling process, significant machining errors may occur due to the low stiffness of thin-walled parts. To reduce the cutting force-induced deformation in milling thin-walled parts such as blades, a cutter orientation optimization algorithm based on stiffness matching is proposed. The concept of maximum stiffness direction is put forward according to the phenomenon that different deformations are produced when applying forces with the same magnitude but in different directions. The stiffness of the in-process workpiece is obtained using the stiffness updating method. The cutter orientation optimization algorithm is presented to match the force with the maximum stiffness direction. The best cutter orientation is obtained by adopting the quantum particle swarms optimization algorithm at the key cutter location points, and then the cutter orientations of all cutter location points are obtained by the quaternion interpolation algorithm. The proposed deformation control method is verified on thin-walled blade milling experiments, and the experimental results show that the machining deformation of the blade with the optimized cutter orientation is reduced by about 36.51%, indicating that the proposed method can effectively reduce the machining deformation of the thin-walled parts.
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      A Deformation Control Method in Thin-Walled Parts Machining Based on Force and Stiffness Matching Via Cutter Orientation Optimization

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4294737
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    contributor authorCai, Yonglin
    contributor authorZhang, Zhengzhong
    contributor authorXi, Xiaolin
    contributor authorZhao, Defu
    date accessioned2023-11-29T19:24:50Z
    date available2023-11-29T19:24:50Z
    date copyright12/2/2022 12:00:00 AM
    date issued12/2/2022 12:00:00 AM
    date issued2022-12-02
    identifier issn1087-1357
    identifier othermanu_145_3_031007.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294737
    description abstractIn the milling process, significant machining errors may occur due to the low stiffness of thin-walled parts. To reduce the cutting force-induced deformation in milling thin-walled parts such as blades, a cutter orientation optimization algorithm based on stiffness matching is proposed. The concept of maximum stiffness direction is put forward according to the phenomenon that different deformations are produced when applying forces with the same magnitude but in different directions. The stiffness of the in-process workpiece is obtained using the stiffness updating method. The cutter orientation optimization algorithm is presented to match the force with the maximum stiffness direction. The best cutter orientation is obtained by adopting the quantum particle swarms optimization algorithm at the key cutter location points, and then the cutter orientations of all cutter location points are obtained by the quaternion interpolation algorithm. The proposed deformation control method is verified on thin-walled blade milling experiments, and the experimental results show that the machining deformation of the blade with the optimized cutter orientation is reduced by about 36.51%, indicating that the proposed method can effectively reduce the machining deformation of the thin-walled parts.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Deformation Control Method in Thin-Walled Parts Machining Based on Force and Stiffness Matching Via Cutter Orientation Optimization
    typeJournal Paper
    journal volume145
    journal issue3
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4056073
    journal fristpage31007-1
    journal lastpage31007-13
    page13
    treeJournal of Manufacturing Science and Engineering:;2022:;volume( 145 ):;issue: 003
    contenttypeFulltext
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