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.     

Prediction of the penetration depth in laser beam welding

Three dimensional solution for the heat flow in laser beam welding with a constant moving Gaussian heat source has been analyzed. The temperature rise and cooling rate are related to the beam spot size, travel speed and laser power. As an application of this model, the theoretical predictions were compared to the experimental data in which laser conditions were arranged for carbon and AISI 316 steels as bead-on-plate welds, using a continous wave 3kW CO₂ laser with the various travel speed, beam sport size and laser power. Experimental data show a good agreement with the theoretical predictions. This analytical model can be used to determine the maximum possible penetration depth, fusion boundary, and thermal history for given sources of laser beam welding conditions.     

CO2激光切割非金属材料理论模型

基于能量平衡方程,考虑高斯光束分布,建立了CO2激光切割高吸收率非金属材料的解析模型。理论分析和试验结果表明切割深度随着切割速度的减小而增加,随着激光功率的增加而增大。该模型适合12mm以下薄板切割和12~20mm较厚板的大功率(>400W)高速(>1.0m/min)切割。经过模型修正后,也可适合厚板(>20mm)切割。     

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.     

A study on laser assisted machining of Ti10V2Fe3Al alloy with varying laser power

Laser-assisted machining (LAM) is a promising technique to improve the machinability of various difficult-to-machine materials such as steels, nickel and titanium alloys and metal-matrix composites. Most of the research studies are focused on analyzing the effect of various cutting parameters such as cutting speeds, feed rates and depth of cut at a constant laser power despite being reported that the maximum benefit of the LAM technique can be realised when all parameters including laser power are optimised. Therefore, the primary objective of this paper is to assess the effect of laser power on the cutting temperature and cutting forces including force fluctuations during the machining of Ti10V2Fe3Al alloy. A cutting force reduction of at least 10 % was found using the assistance of a 1,600 W laser beam between cutting speeds of 55–140 m/min. Nevertheless, it was concluded that a power of 800–1200 W for the laser beam is best suited during LAM of Ti10V2Fe3Al alloy within a cutting speed range of 55–100 m/min. Further, higher cutting speeds were recommended when employing a higher power laser beam to avoid problems such as chatter and chip pile-up.     

Machinability investigation in hard turning of AISI D3 cold work steel with ceramic tool using response surface methodology

The hard turning process has been attracting interest in different industrial sectors for finishing operations of hard materials. In this paper, the effects of cutting speed, feed rate, and depth of cut on surface roughness, cutting force, specific cutting force, and power in the hard turning were experimentally investigated. An experimental investigation was carried out using ceramic cutting tools, composed approximately with (70 %) of Al₂O₃ and (30 %) of TiC, in surface finish operations on cold work tool steel AISI D3 heat-treated to a hardness of 60 HRC. Based on 3³ full factorial designs, a total of 27 tests were carried out. The range of each parameter is set at three different levels, namely, low, medium, and high. Analysis of variance is used to check the validity of the model. Experimental observations show that higher cutting forces are required for machining harder work material. This cutting force gets affected mostly by feed rate followed by depth of cut. Feed rate is the most influencing factor on surface roughness. Feed rate followed by depth of cut become the most influencing factors on power; especially in case of harder workpiece. Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach. It was found that, the use of lower depth of cut value, higher cutting speed, and by limiting the feed rate to 0.12 and 0.13 mm/rev, while hard turning of AISI D3 hardened steel, respectively, ensures minimum cutting forces and better surface roughness. Higher values of depth of cut are necessary to minimize the specific cutting force.     

Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis

This study presents a new method to determine multi-objective optimal cutting conditions and mathematic models for surface roughness (Ra and Rz) on a CNC turning. Firstly, cutting parameters namely, cutting speed, depth of cut, and feed rate are designed using the Taguchi method. The AISI 304 austenitic stainless workpiece is machined by a coated carbide insert under dry conditions. The influence of cutting speed, feed rate and depth of cut on the surface roughness is examined. Secondly, the model for the surface roughness, as a function of cutting parameters, is obtained using the response surface methodology (RSM). Finally, the adequacy of the developed mathematical model is proved by ANOVA. The results indicate that the feed rate is the dominant factor affecting surface roughness, which is minimized when the feed rate and depth of cut are set to the lowest level, while the cutting speed is set to the highest level. The percentages of error all fall within 1%, between the predicted values and the experimental values. This reveals that the prediction system established in this study produces satisfactory results, which are improved performance over other models in the literature. The enhanced method can be readily applied to different metal cutting processes with greater confidence.     

Optimization of cutting conditions for minimum residual stress,cutting force and surface roughness in end milling of S50C medium carbon steel

Residual stresses are usually imposed on a machined component due to thermal and mechanical loading. Tensile residual stresses are detrimental as it could shorten the fatigue life of the component; meanwhile, compressive residual stresses are beneficial as it could prolong the fatigue life. Thermal and mechanical loading significantly affect the behavior of residual stress. Therefore, this research focused on the effects of lubricant and milling mode during end milling of S50C medium carbon steel. Numerical factors, namely, spindle speed, feed rate and depth of cut and categorical factors, namely, lubrication and milling mode is optimized using D-optimal experimentation. Mathematical model is developed for the prediction of residual stress, cutting force and surface roughness based on response surface methodology (RSM). Results show that minimum residual stress and cutting force can be achieved during up milling, by adopting the MQL-SiO₂ nanolubrication system. Meanwhile, during down milling minimum residual stress and cutting force can be achieved with flood cutting. Moreover, minimum surface roughness can be attained during flood cutting in both up and down milling. The response surface plots indicate that the effect of spindle speed and feed rate is less significant at low depth of cut but this effect significantly increases the residual stress, cutting force and surface roughness as the depth of cut increases.     

Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool

Hard turning with multilayer coated carbide tool has several benefits over grinding process such as, reduction of processing costs, increased productivities and improved material properties. The objective was to establish a correlation between cutting parameters such as cutting speed, feed rate and depth of cut with machining force, power, specific cutting force, tool wear and surface roughness on work piece. In the present study, performance of multilayer hard coatings (TiC/TiCN/Al₂O₃) on cemented carbide substrate using chemical vapor deposition (CVD) for machining of hardened AISI 4340 steel was evaluated. An attempt has been made to analyze the effects of process parameters on machinability aspects using Taguchi technique. Response surface plots are generated for the study of interaction effects of cutting conditions on machinability factors. The correlations were established by multiple linear regression models. The linear regression models were validated using confirmation tests. The analysis of the result revealed that, the optimal combination of low feed rate and low depth of cut with high cutting speed is beneficial for reducing machining force. Higher values of feed rates are necessary to minimize the specific cutting force. The machining power and cutting tool wear increases almost linearly with increase in cutting speed and feed rate. The combination of low feed rate and high cutting speed is necessary for minimizing the surface roughness. Abrasion was the principle wear mechanism observed at all the cutting conditions.     

Regression analysis, support vector machines, and Bayesian neural network approaches to modeling surface roughness in face milling

This study examines the influence of cutting speed, feed, and depth of cut on surface roughness in face milling process. Three different modeling methodologies, namely regression analysis (RA), support vector machines (SVM), and Bayesian neural network (BNN), have been applied to data experimentally determined by means of the design of experiment. The results obtained by the models have been compared. All three models have the relative prediction error below 8%. The best prediction of surface roughness shows BNN model with the average relative prediction error of 6.1%. The research has shown that, when the training dataset is small, both BNN and SVR modeling methodologies are comparable with RA methodology and, furthermore, they can even offer better results. Regarding the influence of the examined cutting parameters on the surface roughness, it has been shown that the feed has the largest affect on it and the depth of cut the least.     

Modeling of vapor-to-melt ratio in laser cutting aluminum alloy sheet

To study the regular pattern of vapor-to-melt ratio in laser cutting sheet metal, a physical model of vapor-to-melt ratio is developed to demonstrate the material remove forms of vaporization-melt in cutting area and the state of energy and mass flow in the molten layer. Variation of vapor-to-melt ratio with laser power and cutting velocity is obtained by laser cutting of 6063 aluminum alloy sheet. The 0.5-mm sheet thickness is carried out on a JK701H Nd:YAG pulse laser cutting system by simulating under the regression correction of cut radius. Observation on the cut samples with different parameters (65 W, 85 W, 105 W varied with laser power increasing, and 2.2 mm/s, 2.0 mm/s, 1.8 mm/s with decreasing of beam cutting speed) and the calculations show that vapor-to-melt ratio increases (0.595–1.995, 0.672–2.631, 0.787–4.171) with laser power (65 W–110 W) and decreases with cutting velocity (1.8 mm/s–2.4 mm/s). At the same time, the laser cutting quality increases with vapor-to-melt ratio and the decrease with thickness of residual molten layer. The results show good agreement between vapor-to-melt ratio model and experiments. The analysis verifies that this model is feasible and it makes contribution to laser precision cutting.     

Design optimization of cutting parameters for side milling operations with multiple performance characteristics

In this paper, a grey relational analysis is applied to a set of two-stage experiments designed to determine the cutting parameters for optimizing the side milling process with multiple performance characteristics. The cutting parameters to be considered are cutting speed, feed per tooth, axial depth of cut, radial depth of cut, overhang length and flank wear of peripheral cutting edge. L₃₆ and L₉ orthogonal arrays are used in the experiments and lower-the-better is used as a qualitative characteristic to evaluate the results. It is found that using the grey relational analysis coupled with a deliberate design of the two-stage experiments is simple and efficient in determining an optimal combination of the cutting parameters. The results of the confirmation test also show that this new approach can greatly improve the cutting performance of side milling process.     

Modelling the effects of cutting parameters on residual stresses in hard turning of AISI H11 tool steel

In the present study, an attempt has been made to model the effect of cutting parameters (cutting speed, feed, depth of cut and nose radius) on residual stresses in hard turning of AISI H11 tool steel using ceramic tools. The machining experiments were conducted based on response surface methodology and using the Box–Behnken design of experiments. Residual stresses were determined using the X-ray diffraction technique, and the experimental results were investigated using analysis of variance. The results indicated that the feed and depth of cut are the main influencing factor on residual stresses whereas cutting speed and nose radius are having mild impact on residual stresses. The results show that it is possible to produce tailor-made residual stress levels by controlling the tool geometry and cutting parameters. The aim of this paper is to introduce an original approach for the prediction of residual stresses.     

Using a Nd:YAG laser and six axes robot to cut zinc-coated steel

Zinc-coated steel sheets are important materials in the automobile and home appliance industries. Currently, lasers are the preferred tools for metal cutting because of their good cutting quality, flexibility and excellent features and results, as compared to traditional tools. The solid-state Nd:YAG laser has successfully replaced the gaseous CO₂ laser for metal cutting; its small size and short wavelength makes it suitable for cutting bright and metal-coated materials, as well as being able to be transmitted via optical fibers and robots to cut complicated three dimensional and curved shapes. In this work, the Nd:YAG laser is used to cut 1 mm zinc coated steel sheets. We demonstrate the effects of different cutting parameters such as laser power, cutting speed, different gas types and pressures, and focus position on the cutting quality characteristics of attached dross, kerf width and cut surface roughness. Using a six axes robot, cutting speed was limited to 6 m/min because of the noticeable vibration at higher speeds. Results showed that the cutting surfaces achieved were very sharp and smooth. In cutting, Nd:YAG required less power and attained higher speeds than the published results of a CO₂ laser, which makes Nd:YAG an economical alternative to cut zinc and metal-coated materials. In addition, laser cutting using robots provided efficient and consistent cutting quality, especially in the case of 3D and countered cutting. Apart from using low speed, robots proved to be more economical than costly, specially designed CNC tables.     

Laser hole cutting in Kevlar: modeling and quality assessment

Machining of Kevlar laminates with conventional methods results in poor end-product quality and excessive specific energy requirement for machining. However, laser machining has considerable advantages over the conventional methods due to precision and rapid processing. In the present study, laser hole cutting into Kevlar laminates with different thicknesses and properties is carried out. The laser output power, frequency, and cutting speed are varied during the hole-cutting experiments. The specific energy requirements for cutting, thermal efficiency of the cutting process, and kerf width are formulated and predicted for various laser parameters and Kevlar properties. The cut quality is associated with the damage size around the holes cut and statistical analysis is carried out to examine the affecting parameters on the damaged size. It is found that specific energy requirement is significantly lower than that of the conventional drilling method. The damage size is affected significantly by the laser irradiated power. The quality of holes, as judged by the percentage of damage size around the cut edges cut by a laser beam, is considerably improved compared to the conventional methods.     

Influence of machining parameters on the machinability of particulate reinforced Al/SiC–MMC

The paper presents the result of an experimental investigation on the machinability of silicon carbide particulate aluminium metal matrix composite during turning using a rhombic uncoated carbide tool. The influence of machining parameters, e.g. cutting speed, feed and depth of cut on the cutting force has been investigated. The influence of the length of machining and cutting time on the tool wear and the influence of various machining parameters, e.g. cutting speed, feed, depth of cut on the surface finish criteria has been analyzed through the various graphical representations. The combined effect of cutting speed and feed on the flank wear has also been investigated. The influence of cutting speed, feed and depth of cut on the tool wears and built-up edge is analyzed graphically. The job surface condition and wear of the cutting tool edge for the different sets of experiments have been examined and compared for searching out the suitable cutting condition for effective machining performance during turning of Al/SiC-MMC. Test results show that no built-up edge is formed during machining of Al/SiC-MMC at high speed and low depth of cut. From the test results and different SEM micrographs, suitable range of cutting speed, feed and depth of cut can be selected for proper machining of Al/SiC-MMC.     

Optimisation Technique for Face Milling Stainless Steel with Multiple Performance Characteristics

An optimisation technique for face milling stainless steel based on the Taguchi method with multiple performance characteristics is proposed in this paper. Three cutting parameters namely, cutting speed, feedrate, and depth of cut, are optimised with consideration of multiple performance characteristics including removed volume, surface roughness, and burr height. In this study, not only are the multiple performance characteristics improved, but also the optimal cutting parameters and the weighting factor that significantly affect the multiple performance characteristics are obtained. Experimental results are provided to illustrate the effectiveness of this approach.     

The formation mechanism and the influence factor of residual stress in machining

Residual stresses generated in cutting process have important influences on workpiece performance. The paper presents a method of theoretical analysis in order to explicate the formation mechanism of residual stresses in cutting. An important conclusion is drawn that the accumulated plastic strain is the main factor which determines the nature and the magnitude of surface residual stresses in the workpiece. On the basis of the analytical model for residual stress, a series of simulations for residual stress prediction during cutting AISI 1045 steel are implemented in order to obtain the influences of cutting speed, depth of cut and tool edge radius on surface residual stress in the workpiece. And these influences are explained from the perspective of formation mechanism of residual stress in cutting. The conclusions have good applicability and can be used to guide the parameters selection in actual production.     

Online tool condition monitoring in turning titanium (grade 5) using acoustic emission: modeling

This paper presents an online prediction of tool wear using acoustic emission (AE) in turning titanium (grade 5) with PVD-coated carbide tools. In the present work, the root mean square value of AE at the chip–tool contact was used to detect the progression of flank wear in carbide tools. In particular, the effect of cutting speed, feed, and depth of cut on tool wear has been investigated. The flank surface of the cutting tools used for machining tests was analyzed using energy-dispersive X-ray spectroscopy technique to determine the nature of wear. A mathematical model for the prediction of AE signal was developed using process parameters such as speed, feed, and depth of cut along with the progressive flank wear. A confirmation test was also conducted in order to verify the correctness of the model. Experimental results have shown that the AE signal in turning titanium alloy can be predicted with a reasonable accuracy within the range of process parameters considered in this study.     

Intelligent monitoring and prediction of tool wear in CNC turning by utilizing wavelet transform

In order to realize an intelligent CNC machine, this research proposed the in-process tool wear monitoring system regardless of the chip formation in CNC turning by utilizing the wavelet transform. The in-process prediction model of tool wear is developed during the CNC turning process. The relations of the cutting speed, the feed rate, the depth of cut, the decomposed cutting forces, and the tool wear are investigated. The Daubechies wavelet transform is used to differentiate the tool wear signals from the noise and broken chip signals. The decomposed cutting force ratio is utilized to eliminate the effects of cutting conditions by taking ratio of the average variances of the decomposed feed force to that of decomposed main force on the fifth level of wavelet transform. The tool wear prediction model consists of the decomposed cutting force ratio, the cutting speed, the depth of cut, and the feed rate, which is developed based on the exponential function. The new cutting tests are performed to ensure the reliability of the tool wear prediction model. The experimental results showed that as the cutting speed, the feed rate, and the depth of cut increase, the main cutting force also increases which affects in the escalating amount of tool wear. It has been proved that the proposed system can be used to separate the chip formation signals and predict the tool wear by utilizing wavelet transform even though the cutting conditions are changed.