IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v28y2018i2p178-192.html
   My bibliography  Save this article

Kinematical performance prediction method for rotary axes of 5-axis machine tool in processing of complex curved surface

Author

Listed:
  • Ji-yun Qin
  • Zhen-yuan Jia
  • Jian-wei Ma
  • De-ning Song
  • Li-kun Si

Abstract

The 5-axis machine tool has obvious advantages in processing parts with complex curved surface. Due to the shape complexity of the curved surface and the inflexibility programming of tool orientation, the velocity, acceleration and jerk of rotary axes of 5-axis machine tool always fluctuate significantly during 5-axis high speed machining (HSM), which is one of the important reasons for affecting the quality and the efficiency in 5-axis machining. In this study, a kinematical performance prediction method for rotary axes of 5-axis machine tool is presented, and the velocity, acceleration and jerk of rotary axes during the actual machining can be pre-calculated by it. The prediction method can be easily integrated into the CAM system and can constitute as an indicator for 5-axis trajectory optimisation and feed scheduling. To verify the proposed method, two tests are conducted on a 5-axis milling machine tool controlled by SINUMERIK 840D system, and the prediction results are perfectly matched with the measured results got by 840D system.

Suggested Citation

  • Ji-yun Qin & Zhen-yuan Jia & Jian-wei Ma & De-ning Song & Li-kun Si, 2018. "Kinematical performance prediction method for rotary axes of 5-axis machine tool in processing of complex curved surface," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 28(2), pages 178-192.
  • Handle: RePEc:ids:ijisen:v:28:y:2018:i:2:p:178-192
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=89136
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijisen:v:28:y:2018:i:2:p:178-192. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=188 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.