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author:

Lai, Fuqiang (Lai, Fuqiang.) [1] | Hu, Anqiong (Hu, Anqiong.) [2] | Mao, Kun (Mao, Kun.) [3] | Wu, Zhangbin (Wu, Zhangbin.) [4] | Lin, Youxi (Lin, Youxi.) [5]

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EI

Abstract:

In this paper, the responses of machined surface roughness and milling tool cutting forces under the different milling processing parameters (cutting speed v, feed rate f, and axial cutting depth ap) are experimentally investigated to meet the increasing requirements for the mechanical machining of T2 pure copper. The effects of different milling processing parameters on cutting force and tool displacement acceleration are studied based on orthogonal and single-factor milling experiments. The three-dimensional morphologies of the workpieces are observed, and a white-light topography instrument measures the surface roughness. The results show that the degree of influence on Sa (surface arithmetic mean deviation) and Sq (surface root mean square deviation) from high to low level is the v, the f, and the ap. When v = 600 m/min, ap = 0.5 mm, f = 0.1 mm/r, Sa and Sq are 1.80 μm and 2.25 μm, respectively. The cutting forces in the three directions negatively correlate with increased cutting speed; when v = 600 m/min, Fx reaches its lowest value. In contrast, an increase in the feed rate and the axial cutting depth significantly increases Fx. The tool displacement acceleration amplitudes demonstrate a positive relationship. Variation of the tool displacement acceleration states leads to the different microstructure of the machined surfaces. Therefore, selecting the appropriate milling processing parameters has a positive effect on reducing the tool displacement acceleration, improving the machined surface quality of T2 pure copper, and extending the tool’s life. The optimal milling processing parameters in this paper are the v = 600 m/min, ap = 0.5 mm, and f = 0.1 mm/r. © 2023 by the authors.

Keyword:

Copper Cutting Milling (machining) Surface roughness Topography

Community:

  • [ 1 ] [Lai, Fuqiang]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Hu, Anqiong]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350116, China
  • [ 3 ] [Mao, Kun]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350116, China
  • [ 4 ] [Wu, Zhangbin]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350116, China
  • [ 5 ] [Lin, Youxi]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou; 350116, China

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Source :

Micromachines

Year: 2023

Issue: 1

Volume: 14

3 . 0

JCR@2023

3 . 0 0 0

JCR@2023

ESI HC Threshold:35

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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