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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]

This paper describes an investigation on the optimization of process parameters on the Material Removal Rate (MRR) and kerf in Wire Electrical Discharge Machining (WEDM) operations. The experiments were carried out under varying pulse ON/OFF time, peak current, and wire feed by using Taguchi L9 orthogonal array. Grey Relational Analysis (GRA) optimization technique is used to find the optimal selection of process parameters for improvement in WEDM performance. The deviation of the kerf and material removal rate with process parameters is mathematically modeled by using Response Surface Methodology (RSM). The adequacy of the developed mathematical models is checked by Analysis of Variance (ANOVA). The problem is formulated as a multi-objective optimization as the influence of process input variables on material removal rate and kerf is conflicting in nature. Based on statistical analysis, it has been found that pulse on time, peak current is adequately influential parameters for MRR while pulse off time, peak current, and wire feed adequately influential for the kerf. Confirmation test result shows the application of the optimization technique for predicting optimal combinations of input variables for better output responses.

The present paper deals with the experimental analysis and multi objective optimization of gear cutting process of Inconel 718 using WEDM. The objective of the present work is to optimize the parameters in order to maximize the material removal rate and minimize the kerf in a gear cutting process to get the optimum value. The MRR and kerf play a major role in optimizing the parameters in WEDM process. The experiment is carried out in the wire EDM machine using brass wire as the electrode, Inconel 718 as the work-piece material and distilled water as the dielectric. The design array is created by using Design of Experiment in a Taguchi L16 orthogonal array repeated once. The gear has a base diameter of 20 mm, addendum diameter of 22.5 mm and a pressure angle of 20º with 16 numbers of teeth. The machining operation is carried out by taking 3 input parameters at 4 different levels each. The output parameters such as Material Removal rate and Kerf width were obtained and optimized using TOPSIS method to know the optimum setting. Microstructural analysis of both material and wire were studied to know the various defects during the machining operation. Various plots were obtained to know the effects of the process parameters in WEDM. A regression model was also obtained to validate the statistical model values with the experimental. ANOVA table and Response table were carried out to know the significant parameters and rank respectively in the Wire EDM process. Surface roughness, Addendum and Tooth width of gears were also found out at the optimum settings. The optimum setting of the gear obtained can be used to produce high quality gears and can also be applied for future findings.

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.

This work presents a description of abrasive water-slurry jet machining (AWSJM) to improve machining capabilities of conventional abrasive water jet machine. This work proposes a novel approach of AWSJM, where the conventional abrasive water jet machine (AWJM) is equipped with a liquid (gelatin) polymer solution injection system and a programmable control valve for controlling abrasive flow rate (AFR) and polymer solution flow rate. Parametric study of gelatin enabled AWSJM reveals the improvements in machining performance. Experimental investigations have been performed by varying concentration of the gelatin, pressure of water jet, abrasive flow rate, and abrasive size. The present work identifies the optimal range of process parameters for AWSJM, with natural gelatin as binder, with the response parameters being material removal rate, kerf width, and depth of cut. Gelatin produces a coherent, three-phase, four-content beam of higher kinetic energy in comparison with AWJ and results in increased material removal rate and depth of cut, with reduced kerf width. [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]

Wire electrical discharge machining (WEDM) is one of the most emerging non-conventional manufacturing processes for machining of difficult-to-machine materials. The aim of this book chapter is to present the consolidated information about the contributions of various researchers on WEDM process. This state of art review has been carried out to find out past research work on different materials, influence of process parameters on process performance characteristics and utilization of tools and techniques for correlating experimental results. In addition, this book chapter is concluded by highlighting the optimal ranges of parameters for various materials and indicating the future research directions which will provide a reference to machine tool operators and manufacturing industries depending upon their job requirements. [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]

This paper presents an investigation on the effect and optimization of machining parameters on the kerf (cutting width) and material removal rate (MRR) in wire electrical discharge machining (WEDM) operations. The experimental studies were conducted under varying pulse duration, open circuit voltage, wire speed and dielectric flushing pressure. The settings of machining parameters were determined by using Taguchi experimental design method. The level of importance of the machining parameters on the cutting kerf and MRR is determined by using analysis of variance (ANOVA). The optimum machining parameter combination was obtained by using the analysis of signal-to-noise (S/N) ratio. The variation of kerf and MRR with machining parameters is mathematically modeled by using regression analysis method. The optimal search for machining parameters for the objective of minimum kerf together with maximum MRR is performed by using the established mathematical models. [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]