Progressive segmentation for MRR-based feed-rate optimization in CNC machining

Ka Chun Chan, Charlie C.L. Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Keeping a constant cutting force in CNC machining is very important for obtaining better stability of cutting operation and improving topography, texture and geometry of the machined surface. This paper presents a feed-rate optimization approach based on Material Removal Rate (MRR). Given a tool-path with predefined feed-rates, the geometry of raw material, and the shape of cutter, the histogram of MRR in very fine resolution can be efficiently computed by using a GPU-based geometric modeling kernel. Starting from the evaluation given on the finest histogram of MRR, error-controlled subdivision algorithms are developed to progressively segment the tool-path into user-specified number of sub-regions. Different feed-rates are assigned to different sub-regions so that nearly constant MRR can be achieved while keeping the shape of the given tool-path unchanged. Experimental tests taken on real examples verify the effectiveness of this method.

Original languageEnglish
Title of host publication2015 IEEE Conference on Automation Science and Engineering
Subtitle of host publicationAutomation for a Sustainable Future, CASE 2015
PublisherIEEE Computer Society
Pages691-696
Number of pages6
ISBN (Electronic)9781467381833
DOIs
Publication statusPublished - 7 Oct 2015
Event11th IEEE International Conference on Automation Science and Engineering, CASE 2015 - Gothenburg, Sweden
Duration: 24 Aug 201528 Aug 2015

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2015-October
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference11th IEEE International Conference on Automation Science and Engineering, CASE 2015
Country/TerritorySweden
CityGothenburg
Period24/08/1528/08/15

Keywords

  • Machining
  • Cutters
  • Machine tools

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