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

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

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 tra-jectory 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.

Citation

Syam, W. P., Bansal, R., Benardos, P., Britchford, E., Hopkinson, A., Voisey, K., & Branson, D. T. (2019, September). Image processing algorithm to determine an optimised 2D laser cutting trajectory. Presented at 25th IEEE International Conference on Automation & Computing (ICAC'19), Lancaster, UK

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 25th IEEE International Conference on Automation & Computing (ICAC'19)
• Start Date: Sep 5, 2019
• End Date: Sep 7, 2019
• Acceptance Date: Jun 21, 2019
• Online Publication Date: Nov 11, 2019
• Publication Date: 2019-09
• Deposit Date: Jun 26, 2019
• Publicly Available Date: Jun 26, 2019
• Journal: Proceedings of the 25 th International Conference on Automation & Computing
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 1-6
• Book Title: Proceedings of 25th IEEE International Conference on Automation & Computing (ICAC'19)
• ISBN: 978-1-7281-2518-3
• Keywords: Laser cutting; trajectory optimisation; segmen- tation; amnion; biomaterials; machine vision
• Public URL: https://nottingham-repository.worktribe.com/output/2231639
• Publisher URL: https://ieeexplore.ieee.org/document/8895106
• Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
• Contract Date: Jun 26, 2019