Image processing algorithm to determine an optimised 2D laser cutting trajectory

Wahyudin P. Syam, Ridhi Bansal, Panorios Benardos, Emily Britchford, Andrew Hopkinson, K. T. Voisey, David T. Branson

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

Laser cutting processes offer high-quality and fast cutting capability across a wide variety of materials, including metals, plastics and organic tissues. To enable 2D laser cutting process, a set of (x, y) Cartesian coordinates that form a cutting trajectory have to be given to a machine controller to perform the cutting process. Automatically determining the cutting trajectory from an image of materials with inhomogeneous, crease and transparency characteristics, for example biomaterials, is difficult.In this paper, an image processing algorithm for determining and optimising the trajectory of a 2D laser cutting process is presented. Using this optimised 2D trajectory, uncut material wastes from the laser cutting process can be substantially reduced. The waste reductions are mainly obtained from optimised cutting area allocation and defective cut avoidance by manual cutting. In addition, the presented algorithm accommodates different cutting shapes, determined by a user, to maximise material cut from the laser cutting process.Case studies of thin and transparent amnion biomaterials cutting are presented to demonstrate the proposed algorithm to optimise the 2D laser cutting trajectory of the biomaterials. The algorithm has been tested to determine the optimised 2D cutting trajectory for a rectangle, circle and random shape amnion biomaterials. Results show that uncut materials can be minimised up to 2%, 3% and 5% of the total material of rectangle, circle and random shapes, respectively, by using this algorithm.

Original languageEnglish
Title of host publicationICAC 2019 - 2019 25th IEEE International Conference on Automation and Computing
EditorsHui Yu
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781861376664
DOIs
Publication statusPublished - Sept 2019
Event25th IEEE International Conference on Automation and Computing, ICAC 2019 - Lancaster, United Kingdom
Duration: 5 Sept 20197 Sept 2019

Publication series

NameICAC 2019 - 2019 25th IEEE International Conference on Automation and Computing

Conference

Conference25th IEEE International Conference on Automation and Computing, ICAC 2019
Country/TerritoryUnited Kingdom
CityLancaster
Period5/09/197/09/19

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by Innovate UK (iUK) [grant number 104042] and in collaboration with NuVision Biotherapies Ltd.

Publisher Copyright:
© 2019 Chinese Automation and Computing Society in the UK-CACSUK.

Keywords

  • Amnion
  • Biomaterials
  • Laser cutting
  • Machine vision
  • Segmentation
  • Trajectory optimisation

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