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Kinematics and improved surface roughness model in milling

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Abstract

Surface roughness has a significant influence on the mechanical properties and service life of a component. During face milling, surface roughness greatly varies in the tool step direction and can be controlled by using a surface roughness prediction model. However, the issues of accuracy and efficiency of surface roughness prediction models have not been adequately addressed. This study aims to address these research constraints. An improved surface roughness prediction model is proposed, taking into consideration the influences of insert back cutting and stepover ratio. First, the profile-forming mechanism is analyzed based on geometry and kinematics. Subsequently, an improved surface roughness prediction model is established. Thereafter, the influence of feed per tooth, stepover ratio, corner radius, and minor cutting edge angle on surface roughness are analyzed through numerical simulation. Finally, the experiment of face milling aerospace aluminum alloy 7075 is suggested to verify the improved model, and the Z-Map model is introduced for comparison. Results show that the surface roughness is nonlinear with a feed per tooth and stepover ratio, a monotonic variation with corner radius, and a minor cutting edge angle. The predicted values of the improved model and the Z-Map model for the Rsm are equal to the experimental values. However, the improved model reduces the prediction error of Ra from 11.2 to 4.2% in the non-overlapping compared with the Z-Map model and from 62.58 to 13.34% in the overlapping. In addition, the improved model performs better than the Z-Map model in predicting the shape parameters. This work serves as a significant reference for selecting and optimizing the milling parameters to enable machining quality control.

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Code availability is not applicable to this article.

Abbreviations

R :

Tool of radius (mm)

r :

Corner radius (mm)

t :

Number of teeth

N z :

Maximum number of teeth

Z tn ,c, Ztn, c +1 :

Profile height of the insert in the insert coordinate system (mm)

\({K}_{\mathrm{r}}^{^{\prime}}\) :

Minor cutting edge angle (°)

θ :

Insert contact angle (°)

f z :

Feed per tooth (mm/t)

i :

Forward cutting insert number

k :

Back cutting insert number

a p :

Depth of cut (mm)

K :

Stepover ratio

Y tg :

Position in tool coordinate system

Z W :

Profile height in the workpiece coordinate system (mm)

a e :

Stepping width (mm)

D :

Tool diameter (mm)

B :

Initial cutting width (mm)

S :

Number of stepping

R a :

Profile average height deviation (μm)

S a :

Surface arithmetic mean deviation (μm)

L x :

Length of the workpiece (mm)

L y :

Width of the workpiece (mm)

l :

Insert length (mm)

d :

Insert width (mm)

t m :

Insert thickness (mm)

n :

Rotational speed (rpm)

V :

Feed rate (mm/min)

W :

Width of overlapping (mm)

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Funding

This study was financially supported by the National Natural Science Foundation of China (Grant Nos. 51975305 and 51905289), the Major Science and Technology Innovation Engineering Projects of Shandong Province (Grant No. 2019JZZY020111), the Natural Science Foundation of Shandong Province (Grant No. ZR2020KE027), the National Key Research and Development Plan (Grant No.2020YFB2010500), and the Science and Technology SMEs Innovation Capacity Improvement Project of Shandong Province (Grant No. 2022TSGC1115).

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Authors and Affiliations

  1. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, 266520, China

    Dewei Liu, Changhe Li, Min Yang, Teng Gao, Xiaoming Wang, Mingzheng Liu & Xin Cui

  2. School of Mechanical and Electrical Engineering, Qingdao Binhai University, Qingdao, 266555, China

    Lan Dong

  3. Qingdao Kaws Intelligent Manufacturing Co. Ltd., Qingdao, 266100, China

    Aiguo Qin

  4. State Key Laboratory of Ultra-Precision Machining Technology, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Yanbin Zhang

  5. Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Hafiz Muhammad Ali

  6. Department of Mechanical Engineering, IK Gujral Punjab Technical University, Kapurthala, 144603, Punjab, India

    Shubham Sharma

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  1. Dewei Liu
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Contributions

Dewei Liu: investigation, writing (original draft), and writing (review and editing).

Changhe Li: technical and material support; instructional support, and writing (review).

Lan Dong: collect and organize data and writing (review and editing).

Aiguo Qin: formal analysis and validation.

Yanbin Zhang: formal analysis and validation.

Min Yang: modify paper and formal analysis.

Teng Gao: collect and organize data.

Xiaoming Wang: modify paper and validation.

Mingzheng Liu: modify paper and validation.

Xin Cui: formal analysis and validation.

Hafiz Muhammad Ali: conceptualization and validation.

Shubham Sharma: formal analysis and validation.

Corresponding author

Correspondence to Changhe Li.

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Liu, D., Li, C., Dong, L. et al. Kinematics and improved surface roughness model in milling. Int J Adv Manuf Technol 131, 2087–2108 (2024). https://doi.org/10.1007/s00170-022-10729-8

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