Digital image processing for counting chips in micro-end-milling

Jue Hyun Lee, Angela Sodemann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In conventional milling, the cutting mechanism is dominated by shearing due to the sharp cutting edge. However, it is no longer possible to assume that the cutting edge is sharp in micro-end-milling since the size of the cutting edge of a micro-end-mill becomes comparable to the feed per tooth. As a result, more than one chip formation mechanism occurs in micro-end-milling at the tool-workpiece interface: shearing, elasto-plastic deformation, and ploughing. In the shearing-dominant chip formation, one chip per tooth cut occurs. However, the chip formation mechanism changes into the elasto-plastic deformation or ploughing when the cutting edge of a tool becomes dull due to the tool wear generating no chip per tooth cut. Therefore, the number of chips produced during a cutting operation can be an important indicator of the state of the interaction between a tool and a workpiece. In this paper, the chips from a slot micro-end-milling operation with a 200 tool are counted through digital image processing using Locally Adaptive Threshold Method. In order to count the chips, a chip counting system is developed. The chips are collected and images of the chips are taken by a digital USB microscope. Image processing is applied to the images using Locally Adaptive Threshold Method. The number of chips counted by Locally Adaptive Threshold Method shows less than 10 % counting error.

Original languageEnglish (US)
Title of host publicationProceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450365291
DOIs
StatePublished - Aug 27 2018
Event2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018 - Las Vegas, United States
Duration: Aug 27 2018Aug 29 2018

Other

Other2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018
CountryUnited States
CityLas Vegas
Period8/27/188/29/18

Fingerprint

Milling (machining)
Image processing
Shearing
Plastic deformation
Microscopes
Wear of materials

Keywords

  • Digital image processing
  • Locally adaptive threshold method
  • Micro-end-milling
  • Number of chips

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Lee, J. H., & Sodemann, A. (2018). Digital image processing for counting chips in micro-end-milling. In Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018 Association for Computing Machinery. https://doi.org/10.1145/3271553.3271579

Digital image processing for counting chips in micro-end-milling. / Lee, Jue Hyun; Sodemann, Angela.

Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018. Association for Computing Machinery, 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, JH & Sodemann, A 2018, Digital image processing for counting chips in micro-end-milling. in Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018. Association for Computing Machinery, 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018, Las Vegas, United States, 8/27/18. https://doi.org/10.1145/3271553.3271579
Lee JH, Sodemann A. Digital image processing for counting chips in micro-end-milling. In Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018. Association for Computing Machinery. 2018 https://doi.org/10.1145/3271553.3271579
Lee, Jue Hyun ; Sodemann, Angela. / Digital image processing for counting chips in micro-end-milling. Proceedings of the 2nd International Conference on Vision, Image and Signal Processing, ICVISP 2018. Association for Computing Machinery, 2018.
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