Development of a postprocessor for head tilting-head rotation type five-axis machine tool with double limit rotation axis

  • Qingchun Tang
  • Shaohui YinEmail author
  • Fengjun Chen
  • Shuai Huang
  • Hu Luo
  • Junxiao Geng


The five-axis machine tool with special structure requires the professional postprocessor in order to exploit the capabilities of the machine tools. Compared with the standard five-axis machine, the five-axis machine tools with special structure such as double limit rotation axis (DLRA) requires the implementation of the angle optimization to achieve the process requirements of complex parts. In this paper, a rotation angle optimization algorithm for the DLRA of the head tilting-head rotation (HT-HR)-type five-axis machine tool is proposed to overcome the problem that rotation angle is limited in machining complex parts. First, the initial correction condition is determined based on the rotation range of the rotation axes, in the case that the tool contact point is fixed; the rotation angles of the correction area are optimized. Then, a post processor for HT-HR five-axis machine tool with angle optimization function is developed based on the kinematic model. Furthermore, the proposed approach is validated for simulation and practical experimental with an impeller specimen. Results of the verification tests show that the presented angle optimization algorithm can accurately revise the rotation angle in the processing so as to improve the machining scope of machine tools. This method also provides a certain reference to solve the problem of limited rotation angle for other similar machine.


Double limit rotation axis Five-axis machine tool Rotation angle Postprocessor JAVA 


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The authors thank the reviewers for their valuable comments.

Funding information

This work was supported by the National Natural Science Foundation of China (grant no. 51675171) and the International technology cooperation and exchanges Project (grant no. 2014DFG72480).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Qingchun Tang
    • 1
    • 2
    • 3
  • Shaohui Yin
    • 1
    Email author
  • Fengjun Chen
    • 1
  • Shuai Huang
    • 1
  • Hu Luo
    • 1
  • Junxiao Geng
    • 1
  1. 1.College of Mechanical and Vehicle EngineeringHunan UniversityChangshaChina
  2. 2.Engineering training centerGuangxi University of Science and TechnologyLiuzhouChina
  3. 3.Hunan Provincial Key Laboratory of Intelligent Laser ManufacturingHunan UniversityChangshaChina

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