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PREDICTION OF QUASISTATIC ERRORS IN THREE-AXIS CNC MACHINING CENTERS

  • Xiong-Biao Chen
  • , Aseervadam Geddam

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    Abstract

    Quasistatic error sources, which include thermal, mechanical loading and geometric error sources, are responsible for a very large proportion (typically, 70%) of the volumetric errors of a CNC machine tool. This paper discusses the development of a general quasistatic error model for multi-axis CNC machining centers using rigid body kinematics. To predict the quasistatic errors at any position in the workspace, a new method was proposed using the meshing concepts developed in the FEM literature. Finally, the spatial rate of change of the error was analyzed. The model and analysis method can be used as the basis of a compensation scheme as well as in budgeting of errors on a machine tool. © 1997 American Society of Mechanical Engineers (ASME). All rights reserved.
    Original languageEnglish
    Title of host publicationManufacturing Science and Engineering: Volume 1
    PublisherAmerican Society of Mechanical Engineers
    Pages55-62
    Volume1997-V
    ISBN (Print)9780791826782
    DOIs
    Publication statusPublished - 1997
    EventASME 1997 International Mechanical Engineering Congress and Exposition, IMECE 1997 - Manufacturing Science and Engineering - Dallas, United States
    Duration: 16 Nov 199721 Nov 1997

    Publication series

    NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
    Volume1997-V

    Conference

    ConferenceASME 1997 International Mechanical Engineering Congress and Exposition, IMECE 1997 - Manufacturing Science and Engineering
    PlaceUnited States
    CityDallas
    Period16/11/9721/11/97

    Bibliographical note

    Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

    Funding

    This paper is based on an interim report of Research Project No. 9040090 funded by UGC. The authors are grateful for the support received from the City University of Hong Kong.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure

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