The influence of sulphur content on the quality of laser cutting of steel

Nagels, Els; Duflou, Joost R.; Humbeeck, Jan Van

doi:10.1016/j.jmatprotec.2007.04.103

Cited by 20 publications

(9 citation statements)

References 7 publications

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“…In general, it is clear that the heat affected zone decreases with the smaller values of laser power and increase with the high values of cutting speed. Nagels [10], concentrated on the influence of sulphur content in steel on oxygen assisted CO 2 laser cutting. De-Keuster [11], alluded to the applicability for monitoring purposes of two types of sensors is indicated the microphone and the photodiode.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Optimization of CO2 Laser Turning Process for Armored Steel Assisted by Oxygen

faruk

rezk

Marzouk

et al. 2022

ERJ. Engineering Research Journal

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The current paper investigates the performance of armored steel (500HB) when machined by CO 2 laser turning process (LTP) with oxygen gas assistance for grooving operation. The different working parameters were investigated which include; laser power (P), gas pressure (GP) feed rate (F) and motor speed (S). The different groove dimensions and were considered as the model responses which include; depth of cut (DC), upper cut width (UC) and lower cut width (LC), in addition to the performance aspects of root round error and metal removal rate (MRR). For this purpose, a test rig was designed and fabricated. The experimental results are mathematically modeled by response surface methodology. The results are modeled and illustrated to closely understand the effect and surface quality of CO 2 -LTMP. The optimum process conditions for grooving Armored Steel (500HB) were identified. Results showed that, DC and width of cut and roundness error increase with increasing P and GP, but MRR decreases with increasing F. The motor speed has a moderate effect on the machining process of armored steel under investigation. The optimal combination of machining conditions maximized MRR, DC, LC, UC and minimized root round error to 0.0384 gm, 0.6632 mm, 0.2583 mm, 0.4684 mm and 15.7832 µm respectively. The error between optimum experimental results and the optimum predicted values for MRR, DC, LC, UC and root round error lie within 2.8%, 2.6%, 2.9%, 1% and 6.9%, respectively.

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Section: Introductionmentioning

confidence: 99%

Modelling and Optimization of CO2 Laser Turning Process for Armored Steel Assisted by Oxygen

faruk

rezk

Marzouk

et al. 2022

ERJ. Engineering Research Journal

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“…A significant proportion of heat is concentrated in the molten material and removed from the kerf via the pressurized assist gas [13]. The temperature distribution is localized in the thin cut-edge surface layer and the energy coupling at the workpiece surface is important in terms of determining the cut-edge microstructural properties [14].…”

Section: Introductionmentioning

confidence: 99%

Finite Element Analysis of Laser Cut Edge Beam Section for High Stress Intensity Structural Assessment

Thomas

2016

J Fail. Anal. and Preven.

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This research has analyzed the stability of laser cut-edges in the location of high stress intensity of a structural beam. The cut-edge characteristic properties formed during laser-cutting processing have been over prolonged periods determined to have beneficial effects on fatigue life. During this study two high strength steel grades S355MC and DP600 have been examined. Optimal fatigue lives were attained by minimizing the laser cutedge surface damage, maintaining the formation of shallow striations and by controlling the near edge microstructural deformations during the cutting process. This was validated using a bespoke component in which was tested under four-point loading in which there is a area of stress concentration forming a localized plastic zone. The importance of this region is critical due to the fact that it is the area that influences the fatigue life of the structure. Predicting the lives to crack initiation was determined through FE analysis which is based on the use of E-N cut-edge fatigue data.

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“…1 The machinability, processability and magnetism of steel can be improved through adding appropriate S. However, the content of S in steel shall not be higher than 0.005% (wt) 2 based on the national standards of China. If not, its plasticity and wear resistance would be significantly decreased and even affect the working life of the steel.…”

Section: Introductionmentioning

confidence: 99%

“…Strict and accurate control of nonmetal content, especially the nonmetal elements S and P, plays an extremely important role in determining the mechanical and physical properties of some steels. 1 The machinability, processability and magnetism of steel can be improved through adding appropriate amounts of S. However, the S content of steel should not be higher than 0.005% (wt), 2 based on the national standards of China. If the S content was higher, the steel's plasticity and wear resistance would be signicantly decreased and this may even affect its working life.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of nonmetal elements in steel using laser-induced breakdown spectroscopy combined with random forest

Zhang

Tang

et al. 2015

Anal. Methods

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Laser induced breakdown spectroscopy (LIBS) combined with random forest (RF) was proposed to quantitative analysis sulfur (S) and phosphorus (P) in steel samples. The interference from characteristic spectral line of S and P in steel is difficult to accurately quantitative analysis due to the influence of multi-matrix. RF model was utilized to compensate the negative influence of matrix effect. The influences of laser pulse energy and delay time on the spectral intensity were studied to improve signal-to-noise ratio (SNR) of analytical line for a certain element.Furthermore, the parameters (ntree and m try ) of RF model were optimized by out-of-bag (OOB) estimation. The final RF calibration model for quantitative analysis of S and P in steel was constructed by means of the spectral range (520-620 nm) as input variable under the optimized experimental conditions. Results showed well prediction of RF calibration model for S (R 2 =0.9974) and P (R 2 =0.9981) compared with partial least square regression (PLSR) by using the peak signal of SⅡ545.3 nm and PⅡ602.4 nm, respectively, and the averaged relative error (ARE) of S in steel were 2.69% and 3.47% for 8# and 9# sample respectively, and of P were 1.77% and 0.83% for 8# and 9# sample respectively. This confirms that RF model is a promising approach for quantitative detection of the nonmetal elements with LIBS technology in the field of metallurgy.

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The influence of sulphur content on the quality of laser cutting of steel

Cited by 20 publications

References 7 publications

Modelling and Optimization of CO2 Laser Turning Process for Armored Steel Assisted by Oxygen

Modelling and Optimization of CO2 Laser Turning Process for Armored Steel Assisted by Oxygen

Finite Element Analysis of Laser Cut Edge Beam Section for High Stress Intensity Structural Assessment

Quantitative analysis of nonmetal elements in steel using laser-induced breakdown spectroscopy combined with random forest

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