Efficient toolpath planning for voxel-based cnc rough machining

Aman Kukreja, Mandeep Dhanda, S. S. Pande

Research output: Contribution to journalArticlepeer-review

7 Citations (SciVal)

Abstract

Multi-axis CNC machines are widely used to manufacture complex industrial parts such as dies and molds. The current CNC toolpath planning strategies are complex and often lead to inefficient part programs. This paper presents an approach to use voxel-based CAD models for efficient zig-zag toolpath planning. The developed system focusses on the rough milling of complex parts having multiple machining features. The system takes the CAD (STL) part model and identifies the machinable and non-machinable areas by analyzing the voxelized part model. This follows the segmentation of machinable area into smaller machining regions. Genetic Algorithm is then used to generate an optimum sequence of machining these regions to reduce air cutting path. The developed system was extensively tested using parts with varying machining feature complexities. The system was found to be better than the traditional zigzag roughing toolpath generation methods in terms of the reduction of the number of tool liftoffs and air cutting path length.

Original languageEnglish
Pages (from-to)285-296
Number of pages12
JournalComputer-Aided Design and Applications
Volume18
Issue number2
DOIs
Publication statusPublished - 2020

Bibliographical note

Publisher Copyright:
© 2021 CAD Solutions,.

Keywords

  • CNC rough machining
  • GA based toolpath planning
  • Voxel-based CAD model

ASJC Scopus subject areas

  • Computational Mechanics
  • Computer Graphics and Computer-Aided Design
  • Computational Mathematics

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