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Cutting stress modeling and parameter identification for fine drilling process based on various cutting mechanisms

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Abstract

The superposition effect of various cutting mechanisms (CM) in the fine drilling process brings great challenges to the accurate characterization of the cutting stress field of the workpiece. To solve the above problem, the cutting stress characterization modeling and parameter identification for the fine drilling process with multiple cutting mechanisms is studied in this paper. Firstly, two cutting mechanisms (shear-slip and plough-slip) are distinguished according to the relative tool sharpness (RTS) which is determined by the cutting tool radius and cutting depth, and the fine characterization model for drilling stress of the workpiece is constructed by considering the two cutting mechanisms. Then, in order to overcome the problem that model parameters are difficult to be accurately determined, the sub-interval decomposition optimization method (SDOM) and the improved particle swarm optimization (PSO) are employed to identify parameters in the model. Finally, the proposed method is verified by comparing the single cutting mechanism model, the multiple cutting mechanisms model, and the actual characterization parameter model.

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Abbreviations

σ :

Total stress (MPa)

σ i :

The stress of the i-th cutting element (MPa)

φ :

Half point angle (°)

t c :

The undeformed chip thickness (mm)

r c :

The edge radius (mm)

σ s, τ s :

The normal and tangential stress in shearing zone (MPa)

k s :

The shear yield strength (GPa)

σ max :

The max normal contact stress (MPa)

F v, F f :

The thrust force in the cutting and feed direction (N)

A, B :

The length of the shearing and rubbing zone (mm)

B 1, B 2 :

The length of the first and second rubbing zone (mm)

φ s :

The shear angle (°)

a w :

The cutting width (mm)

σ r, τ r :

The normal and tangential stress in the rubbing zone (MPa)

σ 0, τ 0 :

The max normal and tangential stress of the cutting edge (MPa)

F r 1, F r 2 :

The rubbing force of the flank and rake face (N)

μ :

The friction coefficient

E w, E t :

The elastic modulus of workpiece and tool (MPa)

υ w, υ t :

The Poisson’s ratio of workpiece and tool

F h :

The hydrostatic pressure of the target point (N)

F b :

The physical strength of the workpiece (N)

F t :

The tensile surface traction of cutting boundary points (N)

T :

The temperature (℃)

α :

The linear expansion coefficient of the workpiece (1/℃)

G :

The Green’s functions

S ij, α ij :

The deviatoric stresses and backstresses (MPa)

h, c :

The isotropic hardening coefficient and the kinematic hardening coefficient

κ :

The plastic modulus

p w :

The ploughing thickness of the workpiece (mm)

γ n :

The normal rake angle (°)

X :

The difference degree matrix

X 1 ~ X 6 :

The difference degrees

A act ~ μ act :

The actual characterization parameters

e :

The difference degree evaluation function

mut :

The mutation operator of the elite population

P c, P g :

The two operator selection rates of the normal population

sel c, sel g :

The number of Cauchy mutation and Gaussian mutation

β i :

The weight coefficient of each experimental data

ε i :

The relative error of each predicted and experimental data

C :

The reliability of the models

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Acknowledgements

This research is supported by the State Department project of China (Grant No. JF2020-1-0422). The authors gratefully acknowledge the facilities provided by the Industrial and Intelligent System Engineering Laboratory (IISEL) at the Beijing Institute of Technology.

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Authors and Affiliations

  1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China

    Kuikui Feng, Faping Zhang, Wuhong Wang, Zhenhe Wu, Mengdi Zhang & Biao Wang

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  1. Kuikui Feng
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Contributions

All authors contributed to the conception and design of the study. Kuikui Feng proposed the original modeling and analysis method, Faping Zhang improved the research method, Wuhong Wang conceived the experimental method, and Zhenhe Wu, Mengdi Zhang, and Biao Wang analyzed and organized the experimental data. The first draft was written by Kuikui Feng, and all the authors commented on the previous version. All authors read and approved the final manuscript.

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Correspondence to Faping Zhang.

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Feng, K., Zhang, F., Wang, W. et al. Cutting stress modeling and parameter identification for fine drilling process based on various cutting mechanisms. Int J Adv Manuf Technol 132, 759–779 (2024). https://doi.org/10.1007/s00170-024-13197-4

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