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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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