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Development of a cutting force prediction model based on brittle fracture for carbon fiber reinforced polymers for rotary ultrasonic drilling

  • Songmei YuanEmail author
  • Chong Zhang
  • Muhammad Amin
  • Huitao Fan
  • Ming Liu
Open Access
ORIGINAL ARTICLE

Abstract

Carbon fiber reinforced polymers (CFRP) T700 have got increasing demand in the aerospace industry due to their high specific strength, specific stiffness, and other unique properties. Due to their inhomogeneous, anisotropic, and thermal properties, it is challenging to achieve desired accuracy and to avoid from delamination, chip-off, cracking, and burning especially in the drilling process. The cutting force is the critical parameter which is required to minimize in order to drill a hole with better accuracy and minimize defects. In this research, the brittle fracture approach was adopted and a cutting force model was developed for CFRP-T700 based on the rotary ultrasonic drilling (RUD) process. The experimental RUD was carried out on CFRP-T700 material and found that the feed rate and spindle speed are two main parameters that affect the cutting force in RUD. The cutting force data obtained from the model and experimental setup were then analyzed and found that there is small variation even below 10 % (max value of variation is 8.5 % and the average value is 0.49 %) between simulated and measured values. So, the developed cutting force model was validated and found robust. Also, it was found that with four times increase of feed rate, there is also an increase of material removal rate (MRR) four times with the decrease in the cutting force. Moreover, this model will be much helpful to keep cutting force within limits through the optimal set of parameters as feed rate and spindle speed without extensive experimentation of such costly materials.

Keywords

Carbon fiber reinforced polymers T700 Rotary ultrasonic drilling Cutting force Brittle fracture Cutting parameters 

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Songmei Yuan
    • 1
    Email author
  • Chong Zhang
    • 1
  • Muhammad Amin
    • 1
  • Huitao Fan
    • 1
  • Ming Liu
    • 1
  1. 1.School of Mechanical Engineering and Automation, Beijing Engineering Technological Research Center of High-efficient & Green CNC Machining Process and EquipmentBeihang UniversityBeijingChina

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