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A new energy consumption model suitable for processing multiple materials in end milling

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Abstract

Energy consumption modeling of CNC machine tools is a prerequisite for manufacturers to save energy, reduce environmental pollution, and increase profits. It is of great significance to the healthy development of manufacturing. This paper aims to provide a power model suitable for predicting energy consumption of processing multiple materials in end milling. Firstly, this paper summarizes some limitations in the existing empirical power model of machine tool in cutting state (e.g., the applicability of predicting cutting energy consumption for various materials, the ease of obtaining power model coefficients, and the prediction accuracy of a model). Secondly, the cutting energy is analyzed from the perspective of mechanical mechanics. Combining the empirical and theoretical models analysis, key variables that affect the energy consumption in cutting status were determined. Then, an improved cutting state power model is proposed. The proposed power model is suitable for processing multiple materials in end milling. Thirdly, through experimental research, the effect of key variables on cutting power is discussed, especially its influence on the elastic-plastic term, velocity term, and thermal softening term in the calculation of equivalent shear stress. Suggestions for selecting different empirical power models are also discussed. Finally, the proposed model was verified, and the energy consumption of the end milling process was predicted. The proposed model improved applicability, accuracy, and rapidity to a certain extent of existing empirical models.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgment

This work is financially supported by Science and Technology Planning Project of Guizhou Province of China (No. Qian Ke He Ji Chu -ZK[2021] Yi Ban 274) and Guizhou University of Finance and Economics General Project of School-level Scientific Research Funding (NO.2019XYB10).

Funding

This work is financially supported by Science and Technology Planning Project of Guizhou Province of China (No. Qian Ke He Ji Chu -ZK[2021] Yi Ban 274) and Guizhou University of Finance and Economics General Project of School-level Scientific Research Funding (NO.2019XYB10).

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Authors and Affiliations

  1. College of Big Data Statistics, Guizhou University of Finance and Economics, Guiyang, 550000, China

    Lirong Zhou

  2. Key Laboratory of High Efficiency and Clean Mechanical Manufacture Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, 250061, China

    Fangyi Li, Liming Wang & Geng Wang

  3. Environmental and Ecological Engineering, Purdue University, West Lafayette, IN, 47907, USA

    Yue Wang

Authors
  1. Lirong Zhou
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  2. Fangyi Li
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  3. Liming Wang
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  4. Yue Wang
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  5. Geng Wang
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Contributions

Lirong Zhou is responsible for the study of energy consumption models, the collection and analysis of experimental data, and the writing of papers.

Fangyi Li is responsible for the overall design of the research and article’s framework. Liming Wang is responsible for the design of experimental methods.

Yue Wang is responsible for the translation and revision of the language of the paper.

Geng Wang is responsible for the collection of experimental data.

Corresponding author

Correspondence to Lirong Zhou.

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Zhou, L., Li, F., Wang, L. et al. A new energy consumption model suitable for processing multiple materials in end milling. Int J Adv Manuf Technol 115, 2521–2531 (2021). https://doi.org/10.1007/s00170-021-07078-3

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  • DOI: https://doi.org/10.1007/s00170-021-07078-3

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