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This study investigates the performance of deep cryogenically treated brass (CuZn25Al5) electrodes in the die-sink EDM process. Two different cryogenic treatment durations, 6 h and 12 h, were applied to 8 mm diameter electrodes, and their effects were compared to untreated electrodes. The machining tests were conducted under moderate and aggressive conditions. In the machining tests, the 6-h cryo-treated electrode exhibited a 16.8% increase in material removal rate (MRR) under moderate conditions and a 19.7% increase under aggressive conditions compared to the reference electrode. The 12-h cryo-treated electrode showed similar MRR values to the reference electrode but improved tool wear resistance by 9.4% under moderate conditions. The kerf angle was minimized, indicating better hole verticality, in the 6-h cryo-treated electrode group. The improvement in machining performance was attributed to the enhancement in electrical conductivity of the electrodes, which increased by 28% for the 6-h cryo-treated electrode and 20% for the 12-h cryo-treated electrode. X-ray diffraction (XRD) analysis revealed shifts in peak positions and possible phase transformations due to cryogenic treatment. Surface roughness measurements showed improved surface conditions in the cryo-treated electrodes under aggressive conditions. The results indicate that cryogenic treatment enhances MRR, reduces tool wear, and improves surface quality in die-sink EDM. These improvements are attributed to increased electrical conductivity and changes in the internal structure of the brass electrode. [ABSTRACT FROM AUTHOR]

The high ductility behaviour and high hardening of Nickel–Titanium (NiTi) alloys during cutting make them one of the alloys with low machinability. In addition, poor chip breakage and high tool wear are observed when machining these materials with conventional manufacturing methods. One of the unconventional processing methods, abrasive water jet (AWJ), is an alternative method for cutting low machinability materials. In this study, NiTi shape memory alloy (SMA) was subjected to AWJ drilling under different machining parameters. The aim of the research is to determine the optimum kerf (K), surface roughness (Ra) and material removal rate (MRR) variables resulting from the drilling process by examining the effect of process variables such as water pressure (WP), stand-off distance (SoD) and feed rate used in AWJ machining of NiTi SMAs. Taguchi-based Gray Relational Analysis (GRA), one of the multi-criteria decision-making methods, was used to optimise machining parameters in the drilling of NiTi SMAs with AWJ. The effect percentages of the test levels in the drilling operations were determined using Analysis of Variance (ANOVA). As a result of the experimental study, optimum levels were obtained for K, MRR and Ra at low WP, medium SoD and high feed rate. According to the result obtained from ANOVA, the parameter with the highest effect on K, MRR and Ra was determined as feed rate with 34.65%. [ABSTRACT FROM AUTHOR]

Dicing and filling is the most commonly used method to fabricate the piezoelectric composite by replacing part of the piezoelectric ceramics with the polymer. The dicing quality affects the composite performance, and the dicing mechanism is not clear now. In this study, a theoretical dicing mechanism for PZT-4H ceramics is introduced and validated by the experiments. The results show that, along the dicing depth direction, the dicing surface goes through brittle removal, hybrid of ductile and brittle removal, and pure ductile removal modes. The high wheel speed and low feed rate can help to get the low surface roughness and edge chipping size (width and height) due to the material removal mode transition. The diced kerfs are in saddle shape due to the dicing force variation and wheel vibration in different locations. The composite with high dicing surface quality and consistent size of dicing kerf has low mechanical quality factors variation. The impedance and phase angle at the resonance and anti-resonance frequencies are sharp, which indicates the perfect superposition of the energy from a different pillar. The inconsistent dicing kerf ruined the impedance and phase angle curve after superposition, which shows poor performance. [ABSTRACT FROM AUTHOR]

In this present study, the effect of processing parameters on cutting width (kerf), material removal rate (MRR), Ra (arithmetic mean deviation), Rq (root mean square deviation) and Rz (maximum height) values ​​as a result of wire electrical discharge machining (WEDM) of Ti-6Al-4V alloy was investigated. It is aimed to determine the optimum values of the cutting parameters to obtain the highest MRR value with the lowest kerf, Ra, Rq, Rz. Cutting experiments were carried out using three different voltages (46, 56, 66 V), three different dielectric fluid pressures (10, 12, 14 kg/cm2) and three different wire feed rates (8, 10, 12 m/min). The parameters used in the experiments were designed according to the Taguchi L9 (33) orthogonal array in order to reduce the experimental cost. Gray Relational Analysis (GRA), one of the multi-criteria decision-making methods, has been applied to optimize the machining parameters in the cutting process with the wire erosion machine. Analysis of variance (ANOVA) was used to determine the effect percentages of the processing parameters. By using the data obtained from the experiments, the prediction study of the experimental data was carried out with the Artificial Neural Networks (ANN) model. High correlation coefficients were obtained in the regression model created using the ANN technique, and it was observed that both models were suitable and usable to predict the answers. As a result of GRA, the most ideal sequence was determined as VG1LQ1WS1. Ideal conditions were determined as 46 V voltage, 10 kg/cm2 dielectric fluid pressure and 8 m/min wire feed rate. Using the optimum machining parameters, an improvement of 4.22%, 54.65%, 28.77%, 31.94% and 35.24% was obtained for kerf, MRR, Ra, Rq, and Rz, respectively. As for the results obtained from ANOVA the contribution rate of the voltage was 72.18%. However, the effect of wire feed rate and dielectric fluid pressure was not statistically significant. [ABSTRACT FROM AUTHOR]

The aim of this work is to adopt artificial immune system approach to optimize Abrasive water jet machining parameters during machining on Monel. The process parameters considered are pressure of pump, flow rate of abrasive materials, traverse/cutting speed and standoff distance. In AWJ process parameters plays a crucial role in finding the economics and ability of machining process. The objective behind this experimental study is to conduct a research and analysis of process parameters influence on Kerf and Ra of the Monel 400 work-piece. Taguchi's L16 Orthogonal array approach is used in order to design the experiments to measure the surface roughness and kerf. The order of significance of each input parameters on surface roughness and kerf is determined using Analysis of variance (ANOVA). Multi linear regression model (MLRM) was developed for both kerf and surface roughness. Further, the combined MLRM equation of kerf and surface roughness was optimized using artificial immune system (AIS) algorithm and it was found that at traverse speed of 115.3965 mm/min, stand-off distance of 1.400149 mm, abrasive flow rate of 782.7314 gm/min and pressure of 3686.783 bar were the best set of values to achieve the minimum possible kerf and Ra together. [ABSTRACT FROM AUTHOR]

Laser machining is a cutting-edge thermal energy-based industrial methodology that can be employed to replace the traditional mechanical machining practices in micro-domain applications. In this work, complex hexagonal shape profiles were cut on the surfaces of Nickel-based superalloy (Alloy 276) by fiber optics laser cutting system. Response surface methodology – Central Composite Design approaches were attempted for optimizing laser machining factors to obtain the better output responses. ANOVA was used to identify the significant machining factors which affect the cut quality characteristics. The desirability approach in multi-response optimization was deployed to achieve the minimal kerf width, low surface roughness, minimum heat affected zone while simultaneously increasing the material removal rate. To validate the predicted results obtained from the desirability index analysis, confirmation test was conducted based on a higher desirability index value. The result reveals that the error percentage is less than 5 for all the responses. The results of the confirmation test show that the proposed procedures are effective in improving laser machining parameters for obtaining the better responses. [ABSTRACT FROM AUTHOR]

Bismaleimide-based hybrid fiber composites (BMI) with their expanded thermomechanical properties have been broadly utilized in Aircraft primary applications. The supplanting of carbon fiber with other fiber (kevlar/glass/basalt) is redone to the requirements of the business. To maintain the surface quality, the hybrid composites can be machined with unconventional methods like Abrasive Water jet Machining. In this work, the exploratory examination of interaction boundaries, such as Water pressure (Wp), Transverse speed (Ts), Standoff distance (SOD), Abrasive mass flow rate (ma) of AWJM on hybrid BMI composites was done. Experiments were conducted based on Design of Experiments created from Response surface strategy utilizing Central Composite Design (CCD) and the impact of interaction boundaries on kerf taper and surface roughness were analyzed. The experimental outcomes showed that for the minimum kerf angle, the significant parameters were transverse speed, water pressure, and abrasive flow rate and for minimum surface roughness, transverse speed was the significant parameter. The microstructure analysis revealed that plowing deformation of fiber and abrasive particle embedment at high speed and mass flow rate led to delamination of fiber, which was limited by optimal parameters essentially diminishing kerf taper and surface roughness. [ABSTRACT FROM AUTHOR]

Inconel-625 is a tough-to-cutting material used in ultra-supercritical power plants for flanges, offshore oil sectors, and turbine blades, among other high-temperature components. The objective of this article is to determine the link between four key process independent variables: traverse speed (TSP), abrasive mass flow rate (AMFR), abrasive aqua jet pressure (AAJP), and gap distance (Gd) to the surface roughness (SRa), kerf angle (KEA), and erosion rate (MRR). The response surface methodology-Central composite design (RSM-CCD) was used to perform the experimental interpretations. The influence of individual abrasive aqua jet cutting (AAJC) factors was determined using analysis of variance technique (ANOVA). It was found that AAJP is the dominant factor in the responses. When the AAJP reached its maximum value of 300 MPa, the SRa and KEA reduced by 27.19% and 13.83%, respectively, the MRR improved by 23.71%. The Desirability analysis is handled to optimize the AAJC parameters of Inconel-625. The optimal values of parameters obtained were 300 MPa AAJP, 75 mm/min TSP, 2.4 mm Gd, and 0.55 kg/min AMFR to minimize SRa, KEA, & maximize the MRR. The scanning electron microscope is used to examine the surface morphology and erosion mechanisms. [ABSTRACT FROM AUTHOR]

This study investigates the influence of the stand-off distance (SoD), laser speed (LS) and laser power (LP) on kerf geometry (upper width Wu, down width Wd and kerf angle KA) and mean surface roughness (Ra) during CO2 laser cutting of 3D-Printed Polyethylene-Terephthalate-Glycol (PET-G) thin plates. A full factorial design is implemented, having two levels for SoD and three levels for LS and four levels for LP, resulting in twenty-four (24) cuts. The specimens were manufactured with the Fused Filament Fabrication (FFF) process and had a thickness of 4 mm. First, the Wu, Wd, and KA parameters were measured. Then, the specimens were cut into 24 smaller parts, and the Ra of the processed surfaces was measured. After analyzing the results using descriptive statistical analysis and contour plots corresponding to the two objectives of KA and Ra, a feed-forward and backpropagation neural network (FFBP-NN) was applied. After a series of subsequent training, it was found that the 3-10-2 NN architecture was quite efficient in explaining the variation in terms of the responses, thus having merit in practical applications related to laser cutting. The LC surfaces showed much better Ra (7.2-12 μm) than those in the literature for FFF parts surfaces without post-processing (10.3-30 μm). [ABSTRACT FROM AUTHOR]

In this study, electrode wear caused by machining from cold work tool steel with heat treated 60-62 HRC hardness was investigated by using electro erosion method and Cupro MAX CuCrZr electrode. The workpiece and electrode material are eroded by melting and evaporation as a result of the electrical arc (sparking) that occurs between the electrode and the workpiece in the dielectric environment. These erosions can be interpreted by changes in electrode form measurements and surface roughness. In this context, erosion process was performed using three different current values (6.25, 12.5, 25 A), three different pulse on times (3, 6, 9 µs) and pulse off times (4, 6, 8 µs), respectively, and the electrode wear rate of these processing parameters, the effects on kerf angle and surface roughness were analyzed by macro and analytical measurements. As a result of the analysis, with increasing current, machining time decreased due to increased sparking between workpiece and electrode, but the average surface roughness, kerf angle and wear rate of the electrode increased. It has been determined that as the pulse on time increases, the electrode wear rate decreases. The reduction in electrode wear resulted from the increase in the strength of the electrode due to the protective layer formed by the adhesion of the dielectric fluid and carbon particles released from the workpiece to the electrode surface.

A hybrid approach through combining genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS) for modeling the correlation of laser beam cutting (LBC) parameters and enhancing the quality performance characteristics of machined Hastelloy C276 is emphasized. The LBC experiments are performed by considering gas pressure (GP), cutting speed (CS), pulse energy (PE) and stand-off distance (SOD) as input parameters. The output responses are material removal rate (MRR), kerf taper (KT) and surface roughness (Ra) for the present investigation. The optimal ANFIS training variables are obtained through GA. The training, testing errors, and statistical validation parameter results exposed that the ANFIS learned by GA is outperformed in forecasting LBC responses. In addition, to obtain the optimal combinations of LBC parameters, the multi-response optimization based on maximizing MRR and minimizing KT and Ra was performed using a trained ANFIS network coupled with a whale optimization algorithm (WOA). The responses such as MRR of 236.98 mg/min, KT of 1.135° and Ra of 1.109 µm are forecasted for the optimum cutting conditions: GP of 3 bar, CS of 319.8 mm/min, PE of 5.93 J and SOD of 2.97 mm, respectively. Furthermore, the WOA predicted results are validated by conducting confirmatory experiments. [ABSTRACT FROM AUTHOR]

In this work, two typical surface characteristics, i.e., mean surface roughness and angle of the kerf during laser processing of 3D-printed Polylactic Acid (PLA) plates with 4.00 mm in thickness, are investigated. A carbon dioxide laser was utilized to separate 27 work pieces of rectangular shape. The governing laser parameters, speed of cutting and laser power, were varied according to full factorial experimental methodology. An orthogonal array (OA) having nine combinations was implemented, and nine specimens were cut with the same set-up and the same parameters three times (27 replicates in total). The experimental results were analyzed using descriptive statistical analysis, i.e., histograms, box plots, interaction charts and optimized using analysis of means (ANOM) plots as well as ANOVA analysis. The data analysis indicated that laser speed is the dominant parameter for the kerf angle, whilst both the laser velocity and power are important for mean surface roughness of the cut surface for PLA 3D-printed parts. The spread of the data is smaller in Y direction, which indicates that the weaving phenomenon affects the laser cut performance. [ABSTRACT FROM AUTHOR]

Abrasive water jet (AWJ), which is a non-traditional machining method, is more widely used today. Various materials such as metals, ceramics, polymers, and composites can be easily machined with AWJ. In this study, cutting of St37 steel plates in stacked form with AWJ was investigated. The experiments were carried out according to the general full factorial design. Experimental parameters were inter-stack distance, traverse speed, and abrasive mass flow rate also each of these parameters was chosen at three levels. Surface roughness and kerf widths were examined to determine the cutting performance. Analysis of variance (ANOVA) of all outputs was provided and thus the effects of experimental parameters and their levels on cutting performance were found. The most effective parameters for surface roughness and kerf width in almost all conditions were abrasive mass flow rate and inter-stack distance, respectively. In addition, a concept for multi-simultaneous cutting was developed with mathematical differences of surface roughness and kerf taper angle. Thus, optimum levels of experimental parameters were found for minimum mathematical differences. [ABSTRACT FROM AUTHOR]

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Plasma arc cutting (PAC) process is widely used in metal cutting industries and modern fabrication units. Precise cutting of high strength material is still a challenging task to the industries. PAC process uses thermal energy to melt the material through highly energized plasma gas. Mostly, "hard-to-cut" type materials is used to cut through this process to meet the demands. The present work proposes an experimental investigation of PAC process of hardox 400 and abrex 400. Both the materials are high strength and high abrasion resistance in nature. Experiments were conducted based on Taguchi's L 2 5 orthogonal array design. The cutting parameters analyzed were arc current, cutting speed, stand-off distance and supply gas pressure whereas material removal rate, kerf and surface roughness were selected as responses. Also, a prediction model was developed to estimate the responses using multiple regression analysis. A comparison between experimental and predicted result shows the accuracy of the model. Analysis of variance (ANOVA) was used to verify the effect of each parameter on the surface quality to be assessed. [ABSTRACT FROM AUTHOR]

Demands on better control over the kerf dimension deviation, surface roughness, and corner accuracy are now on the increase for the two-piece aluminum metal composite mold tools. In this investigation, straight and triangular profile cuts attempted with wire electrical discharge machining (WEDM) on the aluminum 6061 self-lubricating composite-reinforced boron carbide (5–15 vol%) and hexagonal boron nitride particles (10 vol% hBN) fabricated using a stir casting method. Rational video measurement showed an increase in B4C particles reduces kerf width dimension deviation only at TON, TOFF and gap voltage (V) parameters. Optical microscope measurement showed an increase in the corner area inaccuracy increases with both low and high pulse-on duration conditions caused by insufficient material removal and a high order of erosion, respectively. There was a large reduction in corner area inaccuracy with increasing wire feed rate. Surface characteristics were examined using a scanning electron microscope (SEM) and XRD to enable observation of the structural damages and recast layers. Composite with 5% boron carbide showed a re-deposition layer over the machined surface, whereas 15% boron carbide composite went through uneven erosion causing the formation of craters and pits on the cutting surface resulting in higher surface roughness. [ABSTRACT FROM AUTHOR]

In plasma cutting, a noble gas at high speed is blown from the nozzle and ionized with the help of a frequency spark at high voltage and an electric arc is created which cause the gas changes to the plasma state. Plasma cutting is an ideal process for cutting of the hard metals. In this research, the effect of the input parameters and their optimization in plasma cutting of AISI 309 stainless steel were studied. By conducting the different experimental tests, the effect of input parameters including amperage, gas pressure and the cutting speed of torch on the three output parameters of the width of cut (Kerf), heat-affected zone (HAZ) and surface roughness (Ra) were investigated. Analysis of the results showed that the amperage, cutting speed and gas pressure have the highest impact on the output parameters, respectively. The artificial neural network (ANN)-genetic algorithm was used to predict and optimize the output parameters. The results indicate that the artificial neural networks model trained by the genetic algorithm are able to predict the output parameters accurately. Finally, the optimization of output parameters to achieve the best cutting conditions was carried out using the genetic algorithm. The artificial neural network models were considered as the objective function and also, the parameters of the heat-affected zone, surface roughness, and the width of cut were introduced as inputs of the algorithm. According to results, a combination of the neural network and genetic algorithm is an efficient method for optimization of the plasma cutting process. This method can be easily modified and utilized for other advanced cutting methods. [ABSTRACT FROM AUTHOR]

In this study machinibility of hardox steel plates (welded by plasma and Mag welding) was examined in WEDM. Two different ampere values and two different feed rates were determined for the two different welding types. Depending on these factors ,micro structures, micro hardnesses and resistivity/conductivity values (varying according to heat output) were obtained at the HAZ and WM zones. Then, each of the samples taken from both HAZ and WM zones were cut in the WEDM by using 2 levelled four different parameters. The purpose at this stage is to examine the cutting width (kerf) and surface roughness (Ra) values at the HAZ and WM zones with respect to varying micro structure, micro hardness and conductivity values. At the end of the study, the lowest kerf was obtained with the plasma welded samples whereas the lowest Ra values were obtained with the Mag welded samples. The samples at WM zone are in general are the ones welded by high conductivity sample Mag welding. Whereas in the HAZ zone the samples are the ones welded by high conductivity plasma welding. [ABSTRACT FROM AUTHOR]

Plasma cutting is an effective way to cut hard metals. In this process, three output parameters cutting width (kerf), surface roughness (Ra) and heat-affected zone (HAZ) are critical factors which affect the quality and efficiency of the cutting. In this paper, an experimental study was conducted to investigate the cutting quality in terms of kerf, Ra, and HAZ for the 309 stainless steel plasma cutting. First, the research tested the effect of input parameters including current, gas pressure, and cutting speed on the process outputs. Then, the results were used to develop three predictive models by intelligent systems based on genetic algorithm (GA) and artificial neural network (ANN). Finally, a hybrid technique of genetically optimized neural network systems (GONNs) was designed and employed to simultaneously optimize the process outputs. The results show that the implemented strategy is an effective method for optimizing the output parameters in the plasma cutting process. [ABSTRACT FROM AUTHOR]

In this study, the machinability characteristics of Al/B4C-Gr hybrid composite were investigated using wire electrical discharge machining (WEDM). In the experiments, the machining parameters of wire speed, pulse-on time and pulse-off time were varied in order to explaiın their effects on machining performance, including the width of slit (kerf) and surface roughness values (Rz and Rt). According to the Taguchi quality design concept, a L18 (21×32) orthogonal array was used to determine the S/N ratio, and analysis of variance (ANOVA) and the F-test were used to indicate the significant machining parameters affecting the machining performance. From the ANOVA and F-test results, the significant factors were determined for each of the machining performance criteria of kerf, Rz and Rt. The variations of kerf, Rz and Rt with the machining parameters were statistically modeled via the regression analysis method. The optimum levels of the control factors for kerf, Rz and Rt were specified as A1B1C1, A1B1C2 and A1B1C2, respectively. The correlation coefficients of the predictive equations developed for kerf, Rz and Rt were calculated as 0.98, 0.828 and 0.855, respectively.

Aluminum metal matrix composites (AMMCs) explicitly show better physical and mechanical properties as compared to aluminum alloys and results in a more preferred material for a wide range of applications. The addition of reinforcements embargo AMMCs employment to industry requirements by increasing order of machining complexity. However, it can be machined with a high order of surface integrity by nonconventional approaches like abrasive water jet machining. Hybrid aluminum alloy composites were reinforced by B4C (5-15 vol%) and solid lubricant hBN (15 vol%) particles and fabricated using a liquid metallurgy route. This research article deals with the experimental investigation on the effect of process parameters such as mesh size, abrasive flow rate, water pressure and work traverse speed of abrasive water jet machining on hybrid AA6061-B4C-hBN composites. Water jet pressure and traverse speed have been proved to be the most significant parameters which influenced the responses like kerf taper angle and surface roughness. Increase in reinforcement particles affects both the kerf taper angle and surface roughness. SEM images of the machined surface show that cutting wear mechanism was largely operating in material removal. [ABSTRACT FROM AUTHOR]

Metal matrix composites are difficult to machine in traditional machining methods. Abrasive water jet machining is a state-of-the art technology which enables machining of practically all engineering materials. This article deals with the investigation on optimization of process parameters of abrasive water jet machining of hybrid aluminium 7075 metal matrix composites with 5%, 10% and 15% of TiC and B4C (equal amount of each) reinforcement. The kerf characteristics such as kerf top width, kerf angle and surface roughness were studied against the abrasive water jet machining process parameters, namely, water jet pressure, jet traverse speed and standoff distance. Contribution of these parameters on responses was determined by analysis of variance. Regression models were obtained for kerf characteristics. Contribution of traverse speed was found to be more than other parameters in affecting top kerf width. Water jet pressure influenced more in affecting kerf angle and surface finish. The microstructures of machined surfaces were also analysed by scanning electron microscopy. The scanning electron microscopy investigations exposed the plastic deformation cutting of hybrid 7075 aluminium metal matrix composite. X-ray diffraction analysis results proved the non-entrapment of abrasive particle on the machined surface. [ABSTRACT FROM AUTHOR]

Composite materials have taken an imperative place in the material system because of their unique performance in various specialized applications. Fiber inclusion and the heterogeneous property of composites make it more difficult to machine with the conventional machining process. However, several nonconventional methods have been adopted for machining composites, in which abrasive water jet machining (AWJM) was proven to be more effective and a preferable technique in machining of fiber-reinforced composite material. This review article is intended to highlight and categorize the machining performance of the fiber-reinforced composites on machining with AWJM process. [ABSTRACT FROM AUTHOR]

Wire Electric Discharge Machining (WEDM) is one of the important non-traditional machining process used for machining difficult to machine materials like composites and inter-metallic materials, Intricate profiles. In the present work, the study has been made to optimize the process parameters during machining of Hastelloy -C-276 by wire-cut electrical discharge machining (WEDM). This paper presents an effective approach to optimize process parameters for Wire electric discharge machining (WEDM) is extensively used in tool and die industries. Precision and intricate machining are the strengths. While machining, time and surface quality still remains as major challenges. The input parameters are pulse on time (Ton), pulse off time (Toff), wire feed rate and current and voltage were changed during the process. The optimization of analysis is performed by using Genetic Algorithm (GA) method L-27 orthogonal array. [ABSTRACT FROM AUTHOR]

This study researched the effects of machining parameters on surface roughness and material removal rate in the wire electrical discharge cutting of high-density Al/B4C metal matrix composites produced via the hot pressing method. Wire tension, reinforcement percentage, wire speed, pulse-on time and pulse-off time were set as the control factors. The Taguchi L18 (21 × 34) orthogonal array was used in the experiment design and determination of the optimum control factors. Variance analysis was applied to determine the effects of the control factors on the surface roughness and material removal rate. The results showed the most effective parameters to be pulse-on time (30.22%) for surface roughness and wire speed (83.20%) for material removal rate, and the optimum levels of the control factors to be A2B1C2D1E1 and A2B2C3D2E2, respectively. Predictive equations were then developed by applying linear regression analysis, and the adjusted correlation coefficients were calculated as 0.61 for surface roughness and 0.785 for material removal rate. [ABSTRACT FROM AUTHOR]

This paper reports the effect and optimization of eight control factors on material removal rate (MRR), surface roughness and kerf in wire electrical discharge machining (WEDM) process for tool steel D2. The experimentation is performed under different cutting conditions of wire feed velocity, dielectric pressure, pulse on-time, pulse off-time, open voltage, wire tension and servo voltage by varying the material thickness. Taguchi's L18 orthogonal array is employed for experimental design. Analysis of variance (ANOVA) and signal-tonoise (S/N) ratio are used as statistical analyses to identify the significant control factors and to achieve optimum levels respectively. Additionally, linear regression and additive models are developed for surface roughness, kerf and material removal rate (MRR). Results of the confirmatory experiments are found to be in good agreement with those predicted. It has been found that pulse on-time is the most significant factor affecting the surface roughness, kerf and material removal rate. [ABSTRACT FROM AUTHOR]

In this article, the effects of varying seven different machining parameters in addition to varying the material thickness on the machining responses such as material removal rate, kerf, and surface roughness of tungsten carbide samples machined by wire electrical discharge machining (WEDM) were investigated. The design of experiments was based on a Taguchi orthogonal design with 8 control factors with three levels each, requiring a set of 27 experiments that were repeated three times. ANOVA was carried out after obtaining the responses to determine the significant factors. The work piece thickness was expected to have a major effect on the material removal rate but showed to be significant in the case of surface roughness only. Finally, optimization of the machining responses was carried out and models for the material removal rate, kerf, and surface roughness were created. The models were validated through confirmation experiments that showed significant improvements in machining performance for all investigated machining outcomes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Samples of 4130 steel were cut on a CO2 laser cutting system and the combined effects of power and feed rate on kerf width, surface roughness, striation frequency and the size of heat affected zone (HAZ) have been studied. Regression analysis was used to develop models that describe the effect of the independent process parameters on laser cut quality. For the range of operation conditions tested, it was observed that power had a major effect on kerf width and size of HAZ, while feed rate affects were secondary. On the other hand, surface roughness and striation frequency were affected most by feed rate. At low power levels, the smallest kerf width and HAZ are obtained and the effect of feed rate is moderate. Low feed rates gave good surface roughness and low striation frequency. For optimum cut quality, kerf width, HAZ and surface roughness are kept at a minimum. However, operating conditions that satisfy these requirements while maintaining high productivity could not be identified. [Copyright &y& Elsevier]

Recently, DC53 die steel was introduced to the die and mold industry because of its excellent characteristics i.e., very good machinability and better engineering properties. DC53 demonstrates a strong capability to retain a near-net shape profile of the die, which is a very challenging process with materials. To produce complex and accurate die features, the use of the wire electric discharge machining (WEDM) process takes the lead in the manufacturing industry. However, the challenge is to understand the physical science of the process to improve surface features and service properties. In this study, a detailed yet systematic evaluation of process parameters investigation is made on the influence of a wire feed, pulse on duration, open voltage, and servo voltage on the productivity (material removal rate) and material quality (surface roughness, recast layer thickness, kerf width) against the requirements of mechanical-tooling industry. Based on parametric exploration, wire feed was found the most influential parameter on kerf width: KW (45.64%), pulse on time on surface roughness: SR (84.83%), open voltage on material removal rate: MRR (49.07%) and recast layer thickness: RLT (52.06%). Also, the optimized process parameters resulted in 1.710 µm SR, 10.367 mm3/min MRR, 0.327 mm KW, and 10.443 µm RLT. Moreover, the evolution of surface features and process complexities are thoroughly discussed based on the involved physical science. The recast layer, often considered as a process limitation, was explored with the aim of minimizing the layers' depth, as well as the recast layer and heat-affected zone. The research provides regression models based on thorough investigation to support machinists for achieving required features. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) laser cutting finds one of its most relevant applications in the processing of a wide variety of polymeric materials like thermoplastics and thermosetting plastics. Different types of polymeric materials like polypropylene (PP), polymethyl methacrylate (PMMA), low- and high-density polyethylene (LDPE, HDPE), are processed by laser for different household as well as commercial products in the industry. The reason is their easy availability and economical aspect in the market. The problems associated with laser cutting include heat-affected zone (HAZ) generated on the cut surface, kerf width (KW), surface roughness (SR), dross formation, and striations formation. Furthermore, other related problems include taper cutting for deep parts and high-power consumption. The primary purpose of this work is a comprehensive literature review in CO2 laser cutting of polymeric materials. The influence of parametric variation on the cut quality is also explained. Cut quality in terms of KW, SR, HAZ, dross formation, and striations formation is analyzed by optimizing cutting variables like laser power (PL), cutting speed (CS), assist gas pressure (Pg), pulse frequency, nozzle type and its diameter, and stand-off distance (SOD). The effects of the laser cutting on the properties of different thermoplastics/thermosetting materials are also reported. However, this topic requires further studies on exploring the range of polymeric materials, and their optimal parameters selection to improve the cut quality. Therefore, the research gaps and future research directions are also highlighted in the context of CO2 laser cutting for polymeric materials. [ABSTRACT FROM AUTHOR]

This paper reports the investigation results of CO 2 laser machining of Inconel 718 superalloy. Investigation on the effects of the two important laser parameters power and travel speed on machinability i.e. material removal rate, kerf wall inclination, and average surface roughness of Inconel 718 has been conducted. Increased kerf wall inclination has been found with slow travel speed and increasing power. Low power and high travel speed produced maximum material removal rate and minimum surface roughness. Premature state of fusion has advanced dross regime at a slow cutting speed of 3.3 m/min and leading to a surface roughness of 9.3 microns maximum. Dendrite structures were formed and changes in surface hardness were observed due to high travel speed. Therefore, based on the investigation, slow travel speed with appropriate laser power is recommended for the improved machinability and surface quality during laser machining of Inconel 718 superalloy. [ABSTRACT FROM AUTHOR]