AI-powered hybrid metaheuristic optimization for predicting surface roughness and kerf width in CO 2 laser cutting of 3D-printed PLA-CF composites DOI
Gökhan BAŞAR, Oğuzhan Der, Mehmet Ali Güvenç

et al.

Journal of Thermoplastic Composite Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 17, 2025

This study explores the impact of CO 2 laser cutting parameters on surface roughness and kerf width 3D-printed Carbon Fiber reinforced Polylactic Acid (PLA-CF) composites while developing phenomenological models using hybrid artificial intelligence techniques. PLA-CF possess certain mechanical properties quality. The values were measured under different conditions (such as plate thickness, power, speed) predicted multiple linear regression, particle swarm optimization-based adaptive neuro fuzzy inference system, ant colony system models. Experimental results showed that are influenced significantly by parameters, showing importance accurately selecting parameters. most dominant factor entered model speed: speed was increased, decreased, but higher levels power resulted in width. Thickness provided a non-linear input: decreased from to 2.5 mm, then increased 4 mm. least (0.809 mm) obtained at 90 W 9 mm/s speed, with mm thickness. Surface minimum (1.878 µm) thickness 3 speed. Among models, gave best accuracy, achieving lowest mean squared error highest correlation coefficient, whereas performed better than regression not optimization. These results, therefore, validate applicability for predicting quality during cutting.

Language: Английский

Tire powder-enhanced jute/epoxy composites: Performance improvement and design optimization for formwork sheathing panel DOI Creative Commons

Meron Solomon Gessesse,

Abrha Gebregergs Tesfay,

Alula Gebresas Gerezgiher

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 483, P. 141661 - 141661

Published: May 14, 2025

Language: Английский

Citations

0
AI-powered hybrid metaheuristic optimization for predicting surface roughness and kerf width in CO 2 laser cutting of 3D-printed PLA-CF composites DOI
Gökhan BAŞAR, Oğuzhan Der, Mehmet Ali Güvenç

et al.

Journal of Thermoplastic Composite Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 17, 2025

This study explores the impact of CO 2 laser cutting parameters on surface roughness and kerf width 3D-printed Carbon Fiber reinforced Polylactic Acid (PLA-CF) composites while developing phenomenological models using hybrid artificial intelligence techniques. PLA-CF possess certain mechanical properties quality. The values were measured under different conditions (such as plate thickness, power, speed) predicted multiple linear regression, particle swarm optimization-based adaptive neuro fuzzy inference system, ant colony system models. Experimental results showed that are influenced significantly by parameters, showing importance accurately selecting parameters. most dominant factor entered model speed: speed was increased, decreased, but higher levels power resulted in width. Thickness provided a non-linear input: decreased from to 2.5 mm, then increased 4 mm. least (0.809 mm) obtained at 90 W 9 mm/s speed, with mm thickness. Surface minimum (1.878 µm) thickness 3 speed. Among models, gave best accuracy, achieving lowest mean squared error highest correlation coefficient, whereas performed better than regression not optimization. These results, therefore, validate applicability for predicting quality during cutting.

Language: Английский

Citations

0