Studies in recent decades show that rapid research has been carried out on WEDM in terms of improving performance measurements, optimizing process parameters, monitoring and controlling the sparking process, simplifying the design and manufacturing of the wire, improving the efficiency by different researchers. The desired work is discussed in more detail in the next paragraphs. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essay Azmir azhari et.al (2017) reported that it is possible to cut polyurethane foam using wire electrical discharge machining (WEDM) process. The foam is made of polyester fabric (PET) coated with copper and nickel. Three different thicknesses of foam constituting different surface and volume resistivities were chosen as the workpiece. The effects of various parameters on the machining length were examined. Process endurance is a high energy loss that periodically leads to wire breakages due to the low electrical conductivity of polyurethane foam. In case of acceleration of the pulse time, the cutting length became shorter since the wire breakage was triggered by a decrease in the discharge frequency. The cutting length increases with increasing pulse dwell time due to sufficient time to remove debris. At higher peak current, the cutting length is exaggerated due to an increase in current dependence. Due to the low servo voltage, the cutting length also decreases, but machining at lower voltages was unstable with frequent wire breaks. Goyal et al (2017) in this investigation study the effect of process parameters on material removal rate (MRR) and surface roughness (Ra). ) in wire EDM machining of Inconel 625. The machining was completed using normal zinc plated wire and cryogenically treated zinc plated wire. The tests were carried out taking into account different process parameters such as tool electrode, current intensity, pulse off time, pulse on time, l yarn feed and yarn tension. The thickness of dia. The wire and the working material remain stable. The Taguchi L18 (21*35) orthogonal array of experimental design is used for the experiments. Analysis of variance (ANOVA) is supposed to optimize the material removal rate and surface roughness. The analysis reveals that pulse time, tool electrode and current intensity are the imperative parameters that affect both MRR and SR parameters. Scanning electron microscopy (SEM) is used to identify the microstructure of the machined part. Singh et al. (2016) reported that for ten years, the wire electrical discharge machining (WEDM) process begins as an unconventional machining process used in manufacturing with complex shapes and varying profiles. However, Al 6063 alloy has countless application fields which inculcate aerospace industry, automobile industries, medical implants, electronics industry, etc. due to its unique and excellent characteristics: high strength-to-weight ratio, high wear resistance, enhanced rigidity, high temperature operation compatibility. temperature and low coefficient of thermal expansion. In this research, experiments were carried out to conduct research to study the effect of process parameters: pulse time, pulse time, servo voltage, peak currenton measuring process performance, i.e., material removal rate (MRR) during WEDM. of the workpiece Al6063. It is evident from the present study that the process input parameters have an indispensable influence on the performance characteristics of the process. The main features of the experimental procedure are also worth noting. Mu-tian yan et al. (2016) worked on the mechatronic system approach for improving the straightness accuracy of parts during roughing of wire EDM machining (wire EDM). The mechatronic system design integrates an active yarn feeding device and a microcontroller-based yarn tension control system into a novel yarn transport system to provide smooth yarn transport and yarn tension value. constant. The active wire feed device was created to reduce the inertia effect of the wire spool on the wire transport system. Then, the PID controller was used to implement real-time yarn tension control of the yarn conveying system. Compared with a conventional yarn transport system, the steady-state error of yarn tension control can be reduced by half with the newly developed system. The ratio of normal sparks to total sparks, defined as the normal spark ratio, can be used to monitor the condition of the spark gap as well as an indication of the evaluation of the machining speed and the precision of the straightness of the parts. Experimental results show that the straightness accuracy of parts can be suitably improved from 13 to 4 µm through the newly developed wire transport system along with optimal machining parameters. G Krishna Mohan Rao et. al. (2014) stated to optimize the metal removal rate of die-sinking electrical discharge machining (EDM) by considering the simultaneous effect of various input parameters. The experiments are carried out on Ti6Al4V, HE15, 15CDV6 and M-250. Experiments were carried out by changing the peak current and servo voltage and the metal removal rate (MRR) values ​​were measured. Multiperceptron neural network models were developed using the Neuro solutions package. The concept of genetic algorithm is used to optimize the network weighting factors. The developed model is expected to be within acceptable error when the results of the experimental and network models are compared for all performance measures considered. It is further observed that the maximum error taken when the network is optimized by a genetic algorithm has been significantly reduced. Sensitivity analysis is also performed to determine the relative influence of factors on performance measures. It is observed that the type of material has more influence on the performance measures.G.Rajyalakshmi et. al. (2013) applied an effective approach, Taguchi gray relational analysis, to the experimental results of wire cutting electrical discharge machining (WEDM) on Inconel 825 considering multiple response measures. The approach combines orthogonal network experiment design with gray relational analysis. The main objective of this study is to achieve improved material removal rate (MRR), surface roughness (SR) and spark gap (SG). Gray relational theory is adopted to analyze the process parameters that optimize the response parameters. The experiment was carried out using Taguchi's L36 (21×37) orthogonal array. Each experiment was conducted under different input parameter conditions. The answer table and the gray relational note for eachlevel of machining parameters have been designed. From 36 experiments, the best combination of parameters was examined. The experimental results show that the method proposed in this study improves the machining performance of the WEDM process. Samar Singh et.al (2012) stated that electric discharge drilling machine (EDDM) is a spark erosion process used for the production of micro holes in conductive materials. materials. This process is widely used in the aerospace, dental, medical and automotive industries. Regarding the performance evaluation of electric discharge drilling machine, it is very important to study the process parameters of the machine tool. In this paper, a brass rod with a diameter of 2 mm was selected as the tool electrode. The experiments generate output responses such as material removal rate. The best parameters such as on time, pulse off time and water pressure have been studied to achieve the best machining characteristics. This research shows the use of the Taguchi approach for better material removal rate when drilling Al-7075. A design of experiments, based on the L27 Taguchi design method, was selected for drilling the material. Analysis of variance (ANOVA) was used to determine the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination of levels and significant drilling parameters on MRR were obtained. Optimization results showed that the combination of maximum pulse on time (Ton) and minimum pulse off time (Toff) results in maximum material removal rate. U. Natarajan et al. (2011) focus RSM for multiple response optimization in micro end milling operations to achieve maximum metal removal rate (MRR) and minimum surface roughness. An aluminum block of 60 × 40 × 16 mm is used as the workpiece material and a carbide cutter of diameter 1 mm as the cutting tool. Jangra Kamal et al. (2010) presented the optimization of performance characteristics in WEDM using Taguchi Gray relational analysis. The process parameters were studied using a mixed L18 orthogonal network. GRA was applied to determine the optimal process parameters for optimization of multiple performance characteristics that were introspected during the rough cutting operation in D-3 tool steel. H. Singh et al. (2009) found that the material removal rate (MRR) increases directly with increasing pulse time and peak current, while it decreases with increasing dwell time of the pulse and servo voltage. They used ELECTRONICA SPRINTCUT WEDM as the machine tool and hot-cast steel (H-11) as the workpiece. Mohammadi and to. (2008) the adjustment of machining parameters relies heavily on the experience of operators and the machining parameter tables provided by machine tool manufacturers. It is difficult to use the optimal functions of a machine due to too many adjustable machining parameters. Kanlayasiri et al. (2007) studied the influences of wire EDM machining variables on the surface roughness of the newly developed DC 53 die steel of width, length and thickness 27, 65 and 13 mm, respectively. Machining variables included pulse time, dwell time, pulse peak current, and wire tension. Variables affecting surface roughness were identified using the ANOVA technique. The results showed that pulse time and pulse peak current were significant variables.