Modelling and prediction of the effect of cutting strategy on surface generation in ultra-precision raster milling

Sujuan Wang, Xin Chen, Suet To, Xindu Chen, Qiang Liu, Jiangwen Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

This paper studies the effect of cutting strategy on surface generation in ultra-precision raster milling (UPRM). By adding the influences of shift length and tool-interference on surface generation, a holistic surface roughness prediction model is built which takes into account the effect of cutting parameters, tool path generation, geometry parameters of diamond tool, the size of the workpiece and machine characteristics. The optimal shift ratio can be achieved by changing factors involved in developing cutting strategy to improve surface quality without decreasing machining efficiency. Conditions for the presence of tool-interference in UPRM are presented. Based on the holistic surface generation model, an integrated system is developed to automatically generate the numerical control program, and predict surface quality and machining efficiency. A series of cutting experiments has been conducted to verify the proposed surface generation model and test the performance of the integrated system. The experimental results agree well with the predicted results from the model and the integrated system.
Original languageEnglish
Pages (from-to)895-909
Number of pages15
JournalInternational Journal of Computer Integrated Manufacturing
Volume30
Issue number9
DOIs
Publication statusPublished - 2 Sep 2017

Keywords

  • cutting strategy
  • surface generation
  • surface roughness
  • ultra-precision raster milling (UPRM)

ASJC Scopus subject areas

  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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