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Influence of blade curvature characteristics on energy consumption in machining process

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Abstract

Saving resources and reducing the energy consumption of CNC machine tools has become one of the main research directions of modern green manufacturing. In this paper, the influence of curvature characteristics on energy consumption is studied based on surface milling. Firstly, the loss of energy consumption in the machining process of the NC machine tool is analyzed, and the milling energy consumption model per unit volume is established; secondly, based on the unit volume milling energy consumption model, a unit volume milling energy consumption model considering blade curvature characteristics is established; finally, based on the milling energy consumption model, the "specific energy" is introduced to establish the energy consumption field model of blade milling path. The distribution of the energy consumption field of four milling paths is analyzed in turn, and the distribution of the energy consumption field of 24 tool sites in the milling path is analyzed. The experimental results show that the energy consumption field model can show the energy consumption distribution of the NC machine tool machining process, and the accuracy is more than 90%, which provides a reliable basis for the subsequent energy consumption prediction of the impeller machining process.

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Availability of data and material

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Not applicable.

Abbreviations

k :

Unit volume cutting energy consumption

u b :

Causes the energy consumption of chips

u s :

Shear deformation energy consumption

u f :

Friction energy consumption between tools and chips

u p :

Energy consumption of new surface produced by workpiece

u k :

Energy consumption caused by chip movement

MRR :

Material removal rate

Vchip :

Chip relative to the speed of the tool

A s :

Mill area cross-sectional area

\(\overline{\tau }\) :

Main shear area average stress

\(\tau\) :

Shear deformation stress of the processed material

k c :

The ratio of actual contact area and appearance contact area

\(\Delta t\) :

Minimum time interval between two points

V s :

The speed of the chip relative workpiece

r b :

Effective cutting radius of the ball head milling cutter

k b :

French curvature along the b direction

\(\mu_{k}\) :

Friction coefficient of each axis of CNC machine tool

a k :

Tool motion acceleration between adjacent two points

w i :

Effective cutting width

P material :

Unit volume removal power

E metaterial :

Unit volume cutting energy consumption

P D :

Unit volume drive power

E D :

Energy consumption due to driving power

F k :

Viscosity friction coefficient of each axis

a e :

Cutting depth

a p :

Cutting width

\(\alpha\) :

Tool front corner

b :

Milling width

t c :

Unclear cutting thickness

F c :

Milling force

V c :

Milling speed

\(\varphi\) :

Shearing angle

\(\beta_{f}\) :

Friction angle

\(\gamma\) :

Shear strain

\(\dot{\gamma }\) :

Shear strain rate

A :

Yield strength

B :

Strain hardening modulus

C :

Strain rate coefficient

n 1 :

Strain hardening index

m :

Heat softening index

T w :

Workpiece temperature

T mrlt :

Material melting temperature

T r :

Room temperature

y s :

Shear area width

v k :

Friction coefficient of each axis

J k :

Inertia of each axis

U :

Specific energy

P i :

Current cutting point

P i + 1 :

Next knife site

v :

Feed speed

f :

Feed direction

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Funding

This research was funded by Projects of International Cooperation and Exchanges NSFC (Grant Number 51720105009).

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Authors and Affiliations

  1. Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin, 150080, China

    Xianli Liu, Linhao Han, Shi Wu, Yue Meng & Caixu Yue

  2. George W, Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, 30332, USA

    Steven Y. Liang

Authors
  1. Xianli Liu
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  2. Linhao Han
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  3. Shi Wu
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  4. Yue Meng
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  5. Caixu Yue
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  6. Steven Y. Liang
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Contributions

Xianli Liu, Linhao Han, Shi Wu, and Yue Meng contributed to the conception of the study. Linhao Han studied the energy consumption modeling of blade machining process. Caixu Yue and Steven Y. Liang helped perform the analysis with constructive discussions.

Corresponding author

Correspondence to Shi Wu.

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Liu, X., Han, L., Wu, S. et al. Influence of blade curvature characteristics on energy consumption in machining process. Int J Adv Manuf Technol 121, 1867–1885 (2022). https://doi.org/10.1007/s00170-022-09420-9

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  • DOI: https://doi.org/10.1007/s00170-022-09420-9

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