Modeling and optimization of kerf taper and surface roughness in laser cutting of titanium alloy sheet

Laser cutting of titanium and its alloys is difficult due to it’s poor thermal conductivity and chemical reactivity at elevated temperatures. But demand of these materials in different advanced industries such as aircraft, automobile and space research, require accurate geometry with high surface quality. The present research investigates the laser cutting process behavior of titanium alloy sheet (Ti-6Al-4V) with the aim to improve geometrical accuracy and surface quality by minimizing the kerf taper and surface roughness. The data obtained from L₂₇ orthogonal array experiments have been used for developing neural network (NN) based models of kerf taper and surface roughness. A hybrid approach of neural network and genetic algorithm has been proposed and applied for the optimization of different quality characteristics. The optimization results show considerable improvements in both the quality characteristics. The results predicted by NN models are well in agreement with the experimental data.     

Effect of process parameters on the cutting quality in lasox cutting of mild steel

Samples of mild steel have been cut on a CO₂ laser machine using the principle of laser assisted oxygen cutting (LASOX). The combined effects of input process parameters (cutting speed, gas pressure, laser power and stand off distance) on cut quality (heat affected zone (HAZ) width, kerf width and surface roughness) have been studied. Regression analysis has been used to develop models that describe the effect of the independent process parameters on cut quality. Using the developed model, we attempted to optimize the input parameters that would improve the cut quality (minimization of HAZ width, kerf width and surface roughness), increase the productivity and minimize the total operation cost. We found from the study that the gas pressure and cutting speed had pronounced effect on cut quality. Low gas pressure produces lower HAZ width, lower kerf width and good surface finish whereas increase in speed results in higher HAZ width, lower kerf width and good surface finish.     

不锈钢板的CO2激光切割工艺研究

实验用CO2激光切割厚0.8mm的1Cr18Ni9Ti不锈钢板。研究了激光功率、辅助气体类型及压力、切割速度对切割质量的影响。实验显示提高切割速度能降低切缝宽度和切口横截面的表面粗糙度;而提高激光功率和氧气压力,切缝宽度也会随之提高,切口横截面更粗糙。功率650~700W、氧气压力0.3~0.5MPa、切割速度3.5~4.5m/min时切割质量最好。另外发现功率在780~1450W,氮气压力低于0.8MPa不能得到良好的切割质量。     

Finite element analysis of laser inert gas cutting on Inconel 718

Inconel 718 has high strength, which makes it difficult to cut using conventional cutting methods. In the present study, the laser inert gas cutting of Inconel 718 was simulated by finite element analysis software ANSYS. Finite element method was used to predict thermal stress and kerf width formation during the laser cutting process. ANSYS Parameter Design Language was used to model the Gaussian-distributed heat flux from the laser beam acting on the workpiece. The removal of melted material during laser cutting to form the kerf width was modeled by employing the element death methodology in ANSYS. In addition, laser cutting was simulated at continuous wave (CW) and the effects of laser power and cutting speed on kerf width were investigated. A series of experiments were carried out to verify the predictions. The temperature fields on the workpiece were measured using thermocouples. The kerf width size was measured using a profile projector, whereas the metallurgical and morphological changes at the cutting edge were examined using scanning electron microscopy. A good correlation was found between the simulation and experimental results.     

Multiple quality optimization in laser cutting of difficult-to-laser-cut material using grey–fuzzy methodology

This paper investigates the laser cutting performance of 1 mm Duralumin sheet with the aim to improve quality of cut by simultaneously optimising multiple performances such as cut edge surface roughness, kerf taper and kerf width. The experimental data obtained by Taguchi methodology-based L₂₇ orthogonal array experimentation have been used in the hybrid approach optimization of grey relational analysis and fuzzy logic theory. The predicted optimum results have been verified by conducting confirmation experiments. The verification results show an overall improvement of 19 % in multiple quality characteristics. The effects of significant factors on quality characteristics have also been discussed.     

Parametric studies on the CO2 laser cutting of Kevlar-49 composite

In the present study, the cutting performance of a CO₂ laser on Kevlar-49 composite materials has been studied. The Taguchi technique is employed to identify the effect of laser control parameters, i.e., laser power, cutting speed, material thickness, assistance gas pressure, and laser mode, on the quality of cut parameters, namely, kerf width, dross height, and slope of the cut. From the analysis of variance (ANOVA) and signal-to-noise (S/N) ratio response tables, the significant parameters and the optimal combination levels of cutting parameters are determined. The obtained results are interpreted and modeled to closely understand the behavior and quality of CO₂ laser cutting. Kevlar-49 composites are found to be cut satisfactorily by the CO₂ laser at the optimum process parameter ranges. The results showed that laser power is the most significant parameter affecting the quality of cut parameters. The optimal combination of cutting parameters minimized the kerf width, dross height, and slope of cut to 0.103 mm, 0.101 mm, and 2.06°, respectively. The error between experimental results with optimum settings and the predicted values for the kerf width, dross height, and slope of cut lie within 2.9%, 7.92%, and 6.3%, respectively.     

RESPONSE SURFACE ANALYSIS OF SLICING OF SILICON INGOTS WITH FOCUS ON PHOTOVOLTAIC APPLICATION

Polycrystalline silicon wafers are widely used in Photovoltaic (PV) industry as a base material for the solar cells. The existing silicon ingot slicing methods typically provide minimum wafer thickness of 300–350 μm and a surface finish of 3–5 μm R_a while incurring considerable kerf loss of 35–40%. Consequently, efficient dicing methods need to be developed, and in the quest for developing new processes for silicon ingot slicing, the wire-EDM (electric discharge machining) is emerging as a potential process. Slicing of a 3′′ square silicon ingot into wafers of 500 μm in thickness has been performed to study the process capability. This article analyzes the effect of processing parameters on the cutting process. The objective of the experimental study is improvement in slicing speed, minimization of kerf loss and surface roughness. A central composite design-based response surface methodology (RSM) has been used to study the slicing of polycrystalline silicon ingot via wire-EDM. A zinc-coated brass wire, 100 μm in diameter, has been used as an electrode in the slicing experiments. It has been observed that the optimal selection of the process parameters results in an increase of 40–50% in the slicing rate along with a 20% reduction in the kerf loss as compared to the conventional methods. The machined surfaces on the sliced wafer were free of micro-cracks and wire material contamination, thereby making it useful for electronic applications.     

Experimental investigation of kerf characteristics through wire electrochemical spark cutting of alumina epoxy nanocomposite

Alumina epoxy nanocomposite (AENC) is an emerging class of composites with a wide range of functionality and applicability; however, managing AENC using a machine is difficult because of its special mixed characteristics. The presence of extremely hard alumina particles in soft epoxy matrix enhances material properties. The present work investigates the kerf characteristics of a straight cut made in AENC through Wire electrochemical spark cutting (WECSC) process. The kerf characteristics, such as kerf deviation and taper, are used to measure the cut quality. The applied voltage, electrolyte concentration, wire velocity, pulse on-time and pulse off-time are varied, and their effects on the kerf characteristics are experimentally investigated in a developed setup. Influencing parameters for straight cutting of AENC are applied voltage, concentration of electrolyte and wire velocity.

     

大角度斜面激光切割加工的工艺研究

分析了大角度斜面激光切割的可行性和激光切割加工工艺。结果表明：当激光功率为1260W，光斑直径为0.18mm,以0.08MPa的氧气作用为辅助气体，切割速度为1.4m/min,使喷嘴离工件的距离保持在0.5mm-0.8mm之间并选取适当的CNC程序直线插补步长，可以实现6mm厚的15Cr2Mo1钢大角度斜面的激光切割，切口质量良好。     

Robust parameter design and multi-objective optimization of laser beam cutting for aluminium alloy sheet

The application of laser beam for precise cutting of sheet metals, in general, and reflective sheet metals, like aluminium, in particular, has become of interest in the recent past. The optimum choice of the cutting parameters is essential for the economic and efficient cutting of difficult to cut materials with laser beams. In this paper, a robust design and quality optimization tool called the Taguchi methodology has been applied to find the optimal cutting parameters for cutting of a reflective sheet made of aluminium alloy with a Nd:YAG laser beam. All the steps of the Taguchi method, such as a selection of orthogonal array, computation of signal-to-noise ratio, decision of optimum setting of parameters, and the analysis of variance (ANOVA), have been done by a self-developed software called computer aided robust parameter design (CARPD). A considerable improvement in the kerf taper (KT) and material removal rate (MRR) has been found by using Taguchi method-based predicted results. Confirmatory experimental results have shown good agreement with predicted results. Further, the Taguchi quality loss function has also been used for multi-objective optimization of laser beam cutting of Al-alloy sheet. The results of multi-objective optimization are compared with the single-objective optimization and it has been found that the kerf taper was increased by 1.60% in multi-objective optimization while the MRR was same in both cases.     

径向基神经网络在三维激光切割中的应用

分析了RBF神经网络的特点，并研究了它在三维激光切割中的应用，利用该神经网络及其变形可以预测切缝的宽度，也可以根据输入参数对试样的挂渣与否进行判定。比较了三雏激光切割中切割倾角和切割方向对切割质量的影响，从而实现切割质量的预测和优化工艺参数的选取以指导实际的切割过程。     

磨料水射流二次逆向切割对断面质量的提升研究

针对磨料水射流切割过程中存在的拖尾余纹、切缝锥度和切割留尾问题，基于磨料水射流切割理论，设计了3组不同因素组合下的单次正向切割、单次1/2速度正向切割和二次逆向切割试验，探讨了3种不同切割方式下的断面形貌产生机理，并对试验结果进行对比分析。结果表明，二次逆向切割可降低表面粗糙度约52%~85%，可降低切缝锥度约66%~72%，同时可消除切割留尾。因此，高压磨料水射流采用二次逆向切割的方式可以显著提高磨料水射流切割工件的断面质量。     

Modeling of wire electro-discharge machining of TiC/Fe in situ metal matrix composite using normalized RBFN with enhanced k-means clustering technique

In the present work, wire electro-discharge machinability of 5 vol% TiC/Fe in situ metal matrix composite (MMC) has been studied. Four input process parameters such as pulse on-time, pulse off-time, wire feed-rate, and average gap voltage have been considered, while cutting speed and kerf width have been considered as the measure of performance of the process. The presence of nonconductive TiC particles and formation of Fe₂O₃ during machining make the process very much unstable and stochastic. Thus, modeling the process either by an analytical or numerical method becomes extremely difficult. In the present study, modeling of wire electro-discharge machining process by normalized radial basis function network (NRBFN) with enhanced k-means clustering technique has been done. In order to measure the effectiveness of this approach, the process has also been modeled by NRBFN with traditional k-means technique, and a comparison has been made between the two models. It is seen that both the models can predict the cutting speed and kerf width successfully, but NRBFN with enhanced k-means clustering technique yields better results than NRBFN with traditional k-means technique. Both the models have been used to carry out the parametric study and, finally, have been compared with the experimental results.     

Effect on Particle Size to Emitted X-Ray Intensity in Pellet Cement Sample Analyzed with WDXRF Spectrometer

Abstract

The particle size and heterogeneity effects on the analyte line were investigated for the analysis of powdered samples by X-ray fluorescence technique. In the analysis of samples utilizing the powder method, these effects caused serious errors with variations in particle size for the emitted intensity. The fluorescence intensities of some elements in pellet samples of cement (the range of particle sizes, < 32 µm, 32–38 µm, 38–45 µm, 45–63 µm, 45–75 µm, 75–106 µm, and 106–150 µm and, at press pressure 3.50 and 1.41 × 10⁷ kg/m²), are measured using a wavelength dispersive X-ray fluorescence (WDXRF) spectrometer for 14 pellets prepared according to the powder method. The results show that the K _α X-ray fluorescence intensities from samples can effect about 17% maximum differences in normalized intensities within selected particle sizes. These experimental results were interpreted by comparing with the other experimental results in the literature.     

Single and dual gas jet effect in Ytterbium-doped fibre laser cutting of dry pine wood

This paper presents single and dual assist gas jet effects in the single-pass laser cutting of dry pine wood. The laser wood cutting process is influenced by the assisting gas jet(s) applied. Therefore, it is important to understand their roles in the removal of fumes and combusted materials from the cutting kerf. A computational fluid dynamic model is developed to investigate the effect of single and dual gas jets in the laser wood cutting process. In order to obtain a close approximation of the actual process, a three-dimensional model was considered. Results obtained in the simulations were compared with experimental data collected from a multifactor experiment analysing the laser cutting process of dry pine wood. A high brightness, 1?kW IPG single-mode, continuous-wave Ytterbium fibre laser was employed to cut cubic wood samples parallel to the wood fibre direction. It has been found that shear stresses produced by the gas jet(s) on the kerf walls have an important correlation with the yield and cut quality.     

Modeling cutting machining process using symbolic regression \alpha -\beta

An analysis of a cutting machining process is made by manipulating equations generated by means of symbolic regression $\alpha $ - $\beta $ . This regression approach can generate mathematical models of any process considering only measured data. Usually a mathematical model is preferred over other approaches like linear regression or neural networks. As a practical case, a cutting machining process of Titanium 6Al-4V is modeled considering the absence and existence of cooling. An analysis of the surface of response is made to visualize the effects of the machining parameters on roughness. These plots could be useful to establish the machining parameters when a desirable roughness is expected. On the other hand, the mathematical models can be useful for prediction, simulation and optimization.     

CO2 laser cutting of Kevlar laminate: influence of assisting gas pressure

In the present study, laser cutting of Kevlar laminate is considered, and the effect of assisting gas pressure and laser output power on the end product quality is examined. The end product quality is judged via measurement of out-of-flatness and kerf width ratios. Experimental tests are carried out using a CO₂ laser beam with pulse repetition rate of 300 Hz. The cutting model introduced previously is accommodated to predict the kerf size for various laser output power and assisting gas pressures. The predictions are compared with the experimental results. It is found that the predictions of kerf size are in good agreement with the experimental results. The influence of assisting gas pressure is significant on the resulting cut quality, in which case, out-of-flatness and kerf width ratio improve considerably at high assisting gas pressures (500 kPa).     

Laser cutting of 7050 Al alloy reinforced with Al2O3 and B4C composites

In the present study, laser cutting of 7050 aluminum alloy sheets reinforced with Al₂O₃ and B₄C particles are carried out. The cut geometry is examined using scanning electron microscope and the optical microscope. The lump parameter analysis technique is used to formulate and determine the kerf width size. The predictions for kerf width are compared with experimental data. The percentage kerf width size variation along the cut edges is determined and the influence of the laser power level and duty cycle of the laser pulses on the percentage kerf width size variation is examined. It is found that 7050 aluminum alloy reinforced with 20% Al₂O₃ composite results in relatively large kerf width size as compared to its counter parts that corresponding to 7050 aluminum alloy reinforced with 20% B₄C composite. The kerf width size predicted agreed with the experimental data for both composites.     

Identification and quantification of β-caryophyllene in copaiba oil using Raman spectroscopy

Copaiba oleoresin presents several compounds with known biologic activity and physiologic effects, including analgesic and insecticide properties. Among them are the terpenoids (mainly diterpenes and sesquiterpenes) with β-caryophyllene, the main representative of the terpenoids and considered to be a chemical marker. This study employed Raman spectroscopy and principal component analysis (PCA) techniques to identify and quantify the β-caryophyllene marker in copaiba oil samples purchased from popular markets in Brazil. A dispersive Raman spectrometer (830?nm, 250?mW, 2?cm^?1 spectral resolution) was used. Results showed the identification of the main Raman peaks from the β-caryophyllene in copaiba oil samples (main peaks at 507, 771, 1442, 1638, and 1673?cm^?1). The loading vector 2 (PC2) extracted the spectral information from β-caryophyllene in the samples and the eigenvalue 2 (score 2) allowed the estimation of the concentration of this marker in commercial samples, with the concentrations from 15 to 34%. Raman spectroscopy combined with PCA may be considered to be a potential analytical tool for the quality control of Copaifera oil samples by quantifying β-caryophyllene using its unique spectral information.     

Determination of Ammonia in Seawater by Multichannel Flow Injection Analysis

An analytical method that uses multichannel flow injection is reported to determine ammonia in seawater. The sample throughput was twenty-eight samples per hour. The linear dynamic range for ammonia was from 20.0–1000.0 μg N · L^?1 with a limit of detection of 0.27 μg N · L^?1, and recovery values between 98.1% and 104.6%. The relative standard deviation values for nitrogen as ammonia were 2.15–3.33% (n = 6). Statistical t-test analysis indicated that analysis by the flow injection method provided results that were statistically the same as standard procedures. The reported method was suitable for the determination of ammonia in seawater.