- Journal of Materials and Mechatronics: A
- Cilt: 4 Sayı: 2
- Statistical Investigation of the Effect of CO2 Laser Cutting Parameters on Kerf Width and Heat Affec...
Statistical Investigation of the Effect of CO2 Laser Cutting Parameters on Kerf Width and Heat Affected Zone in Thermoplastic Materials
Authors : Oğuzhan Der, Gökhan Başar, Muhammed Ordu
Pages : 459-474
Doi:10.55546/jmm.1359453
View : 71 | Download : 83
Publication Date : 2023-12-26
Article Type : Research
Abstract :Understanding and optimizing the CO2 laser cutting process of thermoplastic materials is critical for improving product quality, reducing waste, and achieving efficient manufacturing processes. This study aimed to investigate the effects of a number of input parameters (i.e., material type, power, and cutting speed) on the key output parameters (i.e., kerf width and heat affected zone) in CO2 laser cutting of thermoplastic materials. The laser cutting process was performed based on the Taguchi L18 (21x32) orthogonal array design. The effects of cutting parameters on the outputs were calculated by using the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) techniques. Furthermore, first and second-degree mathematical models were established by using regression analysis to estimate the values of kerf width and heat affected zone. The optimum laser cutting parameters for kerf width and heat affected zone were determined as and Polyvinyl Chloride (PVC) material type, 80 W power, and 15 mm/s cutting speed. The ANOVA results showed that the most efficient parameter on kerf width was power with 53.99% while the most efficient parameter on heat affected zone was material type with 40.96%. In addition, the coefficient of determination (R2) values for the regression equations developed for the outputs are significantly high. The R2 values of the first- and second-degree regression equations for KW are 97.26% and 99.71%, respectively, whereas 93.43% and 98.18% for HAZ.Keywords : CO2 Lazer Kesim, Kerf Genişliği, Isıdan Etkilenen Bölge, ANOVA, Regresyon Analizi