Effect of process parameters on machinability characteristics of CO2 laser process used for cutting SS-304 Stainless steels

2019 ◽  
Vol 18 ◽  
pp. 2065-2072
Author(s):  
K. Rajesh ◽  
V.V. Murali Krishnam Raju ◽  
S. Rajesh ◽  
N. Sudheer Kumar Varma
2013 ◽  
Vol 316-317 ◽  
pp. 1007-1013 ◽  
Author(s):  
Heng Fu Xiang ◽  
Li Jun Zhang

CO2 laser rapidly patterning microfluidic chips on polymer substrate with direct writing ablation had attracted many experts from domestic and foreign in resent years. This method had features of flexible, rapid, easily controllable and high efficient, and was regarded as the most potentialized fabrication method to improve the development of microfluidic systems. This paper systematically reviewed polymer substrate materials, the mechanism of laser and material, fabrication models and factors influenced the fabrication process, as well as the influence on microfluidic chips fabrication quality by laser process parameters. Moreover, the existent problems and possible resolutions based on the mechanisms of interactions between laser and materials was analyzed.


1996 ◽  
Author(s):  
Herve L'Enfant ◽  
Patricia Laurens ◽  
Marie C. Sainte Catherine ◽  
Jacques Amouroux

Author(s):  
Alessandro Fortunato ◽  
Leonardo Orazi ◽  
Giovanni Tani

The bottleneck in laser hardening principally occurs when large surfaces have to be treated because this process situation leads to multi-tracks laser scanning in order to treat all the component surface. Unfortunately, multi-tracks laser trajectories generate an unwanted tempering effect that depends on the overlapping of two close trajectories. To reduce the softening effects, a simulator capable to optimize the process parameters such as laser power and speed, number and types of trajectories, could sensibly increase the applicability of the process. In this paper an original model for the tempering is presented. By introducing a tempering time factor for the martensitic transformation, the hardness reduction can be predicted according to any laser process parameters, material and geometry. Experimental comparisons will be presented to prove the accuracy of the model.


2015 ◽  
Vol 88 (1) ◽  
pp. 125-137 ◽  
Author(s):  
Shib Shankar Banerjee ◽  
Anil K. Bhowmick

ABSTRACT The application of the low-power CO2 laser-cutting process to fluoroelastomer (FKM), polyamide 6 (PA6), PA6/FKM thermoplastic elastomers (TPEs), and their thermoplastic vulcanizate (TPV) is reported. The main laser process parameters studied were laser power, cutting speed, and material thickness. The value of the top and bottom widths of the slit that were formed during laser cutting (kerf width), melted transverse area, and melted volume per unit time were measured and analyzed. Interestingly, TPE showed a smaller melted area and melted volume per unit time when compared with those values with PA6. Dynamic vulcanization further decreased these values. For example, the melted areas of PA6 and TPE were 510 × 10−3 mm2 and 305 × 10−3 mm2, respectively, which reduced to 238 × 10−3 mm2 for TPV at 40 W laser power. FKM showed the lowest value (melted area of 180 × 10−3 mm2). In addition, the output quality of the cut surface was examined by measuring the root mean square (RMS) roughness of the cut edges and heat-affected zone (HAZ). The obtained results indicated that the dimension of the HAZ and RMS roughness largely decreased in TPE when compared with PA6. For example, the HAZ of PA6 was 700 μm, which decreased to 230 μm for TPE at 40 W laser power. On the other hand, HAZ was nonexistent for FKM. Infrared spectroscopic analysis showed that there was no structural change of TPE or pristine polymers after applying the low-power CO2 laser on the surface of materials. CO2 laser cutting will be a new technique in this industry, and this analysis will assist the manufacturing industry to choose a suitable laser system with exhaustive information of process parameters for cutting or machining of rubber, TPEs, and TPVs.


2012 ◽  
Vol 44 (4) ◽  
pp. 1068-1082 ◽  
Author(s):  
H.A. Eltawahni ◽  
M. Hagino ◽  
K.Y. Benyounis ◽  
T. Inoue ◽  
A.G. Olabi

2019 ◽  
Vol 342 ◽  
pp. 371-379 ◽  
Author(s):  
Dongsheng Sun ◽  
Dongdong Gu ◽  
Kaijie Lin ◽  
Ji Ma ◽  
Wenhua Chen ◽  
...  

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