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Capability Enhancing of CO2 Laser Cutting for PMMA Sheet Using Statistical Modeling and Optimization

Authors :
Mahmoud Moradi
Mohammad Rezayat
Saleh Meiabadi
Mojtaba Karamimoghadam
Stephen Hillyard
Antonio Mateo
Giuseppe Casalino
Zammad Tanveer
Muhammad Adnan Manzoor
Muhammad Asad Iqbal
Omid Razmkhah
Source :
Applied Sciences, Vol 13, Iss 23, p 12601 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Laser cutting is a widely used manufacturing process, and the quality of the resulting cuts plays a crucial role in its success. This research employed the Design of Experiments (DOE) to investigate the impact of input process parameters on kerf quality during the laser cutting of 5 mm polymethyl methacrylate (PMMA) sheets. Response surface methodology (RSM) was utilized to model the relationship between the input parameters and the kerf quality, with regression equations developed for each response using the Design Expert software. A statistical analysis revealed the significant effects of high laser power, cutting speed, and focal plane position on kerf quality. Optimization, guided by the desirability function, identified optimal parameter combinations that offered the most favorable tradeoff among various responses. Optimal conditions were found to involve a high laser power, a cutting speed ranging from 4 to 7 mm/s, and a focal plane position at the center. Experiments indicated the suitability of the models for practical applications. An overlay plot analysis revealed a weak negative correlation between the laser power and the cutting speed, while the focal plane’s position could be adjusted independently.

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
23
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.206285611b0a4bfe9416b658932ae35b
Document Type :
article
Full Text :
https://doi.org/10.3390/app132312601