Simulation, statistical modeling, and optimization of CO2 laser cutting process of polycarbonate sheets

Moradi, M., Moghadam, M.K., Shamsborhan, M., Beiranvand, Z.M., Rasouli, A., Vahdati, M., Bakhtiari, A. and Bodaghi, M. ORCID: 0000-0002-0707-944X, 2020. Simulation, statistical modeling, and optimization of CO2 laser cutting process of polycarbonate sheets. Optik: 164932. ISSN 0030-4026

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Abstract

Laser cutting well-known as a manufacturing process is a rapid, repeatable, and reliable method that is frequently used for cutting various materials such as thermoplastics. Due to their physical and chemical properties such as fatigue resistance, high toughness, and remelting properties, thermoplastics such as polycarbonate are widely used in automotive parts, electronics, etc. In this study, a numerical simulation of the laser cutting process by a finite element method is developed. The sample simulated in this research is a 3.2 mm thick Polycarbonate sheet that is subjected to the laser cutting process by a low power continuous CO2 laser. The effects of the laser cutting process parameters such as laser power, cutting speed, and laser focal plane position on the top and bottom kerf width, top heat-affected zone, the ratio of upper kerf width to lower kerf width and taper kerf are investigated by statistical techniques of variance analysis. Choosing an appropriate Gaussian distribution is studied as well. The results show that the laser scanning speed has a significant effect on the top kerf width. By choosing a cutting speed of 20 mm/s and a focal length of -3, the taper kerf is minimized. By increasing the laser cutting speed from 4 to 20 mm/s and decreasing the laser power from 50 to 20 Watts, the heat-affected zone decreases. The developed analysis can predict the depth of kerf in a continuous mode for different values of laser power, speed, and laser focal plane.

Item Type: Journal article
Publication Title: Optik
Creators: Moradi, M., Moghadam, M.K., Shamsborhan, M., Beiranvand, Z.M., Rasouli, A., Vahdati, M., Bakhtiari, A. and Bodaghi, M.
Publisher: Elsevier BV
Date: 27 May 2020
ISSN: 0030-4026
Identifiers:
NumberType
10.1016/j.ijleo.2020.164932DOI
S0030-4026(20)30768-3Publisher Item Identifier
1329576Other
Divisions: Schools > School of Science and Technology
Depositing User: Jill Tomkinson
Date Added: 02 Jun 2020 15:49
Last Modified: 02 Jun 2020 15:49
URI: http://irep.ntu.ac.uk/id/eprint/39928

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