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Specific cutting energy index (SCEI)-based process signature for high-performance milling of hardened steel

  • Zerun Zhu
  • Fangyu Peng
  • Xiaowei TangEmail author
  • Rong Yan
  • Zepeng Li
  • Chen Chen
  • Hao Sun
ORIGINAL ARTICLE
  • 6 Downloads

Abstract

The specific cutting energy can characterize the machinability of the cutter for a material, and its change is a reflection of the size effect in the metal cutting process. It is critical to study the cutting process using an energy-based processing signature method with the purpose of improving the machining performance. In this paper, a specific cutting energy calculation method is presented based on a mechanistic model, and an exponential function is used to describe the trend in the specific cutting energy with the average undeformed chip thickness. A dimensionless index with value of greater than 1, referred to as the Specific Cutting Energy Index (SCEI), is proposed to address the energy efficiency of the milling process and reflect the machining performance for different machining parameters. Machining experiments with 300 M steel are conducted to validate the effectiveness of the proposed model. Analyses are performed to determine the relationships between SCEI and the material removal mode, chip morphology, tool wear rate, and surface roughness. Based on these results, a feed rate scheduling method is proposed to obtain optimal machining strategies using SCEI, which is an effective way to achieve high-performance machining.

Keywords

Specific cutting energy Process signature Milling Parameter selection 

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Notes

Funding information

This research has been supported by the National Science Fund for Distinguished Young Scholars of China under Grant No. 51625502, Innovative Group Project of National Natural Science Foundation of China under Grant No. 51721092, and Innovative Group Project of Hubei Province under Grant No. 2017CFA003.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Zerun Zhu
    • 1
  • Fangyu Peng
    • 2
  • Xiaowei Tang
    • 1
    Email author
  • Rong Yan
    • 1
  • Zepeng Li
    • 1
  • Chen Chen
    • 1
  • Hao Sun
    • 1
  1. 1.School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhanChina
  2. 2.State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhanChina

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