4.4 Article

Experimental study on micromilling deformation control of micro-thin wall based on the optimal tool path

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s40430-021-02962-1

Keywords

Mesoscopic scale; Micro-thin wall; Optimal tool path; Deformation control

Funding

  1. Doctoral Research Fund of Shandong Jianzhu University [XNBS1809]
  2. Natural Science Foundation of Shandong Province [ZR2020QE180, ZR2019MEE029]
  3. Key Research and Development Project of Shandong Province [2018GGX105008]
  4. Fundamental Research Funds for the Central Universities [G2020KY0501]
  5. Foundation Research Project of Taicang City [TC2020JC10]

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This paper explores the deformation control of micro-thin-walled materials during milling, proposing new strategies and conducting experiments to verify their effectiveness. The study aims to improve machining accuracy of micro components and provides valuable insights for future research in this area.
At the mesoscopic scale, the milling deformation of complex components with micro-thin-walled features such as micro-channel cold plates and aerospace honeycomb materials is the main factor affecting their machining accuracy. In order to effectively control the deformation in the process of milling and improve the machining accuracy of micro-thin wall, this paper starts with improving the stiffness in the milling process of micro-thin wall. Firstly, the deformation control method based on the optimal tool path is proposed during milling the micro-thin wall, including the deformation control of micro-thin wall with cantilever boundary in asymmetric step milling and the deformation control of micro-thin wall with complex boundary in piecewise variable feed milling; secondly, a lots of micro-thin-walled milling experiments are carried out with different milling parameters, tool paths and cooling methods; finally, compared with the free milling, the thickness and surface morphology of micro-thin wall after milling under the two control strategies are analyzed to verify the effectiveness of the control strategy and determine the optimal control strategy.

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