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The study investigates the influence of Wire-cut Electrical Discharge Machining (WEDM) input variables on the Ni–Cu superalloy, crucial in marine environments. Input variables include Input current (Ic), Pulse on Time (TON), Pulse off Time (TOFF), Servo Voltage (SV), and Wire Feed (WF) rate, while output variables are Machine Speed (Mc), Kerf Width (K), and Material Removal Rate (MRR). Utilizing an L16 orthogonal matrix, experiments were conducted. The Taguchi method examines single output variables, while the Grey Relational Grade Algorithm (GRA) assesses multi-objective outputs. GRA identifies optimal input combinations, crucial for maximizing the machining performance. ANOVA of GRA results highlights Pulse on Time (TON), Input current (Ic), and Servo Voltage (SV) as significant factors affecting Mc, K, and MRR. This analysis underscores their importance in optimizing the WEDM process for Ni–Cu (MONEL K-500 superalloy). [ABSTRACT FROM AUTHOR]

This study aims to optimize the Wire Electrical Discharge Machining (EDM) process parameters for aluminum 6061 alloy reinforced with Mg and MoS2 using the Box–Behnken (BBD) design and the non-dominated sorting genetic (NSGA-II) algorithm. The objective is to enhance the machining efficiency and quality of the composite material. The Box–Behnken (BBD) design was utilized to design a set of experiments with varying levels of process parameters, comprising pulse-on time, servo volt, and current. The material removal rate and surface roughness were considered as machining responses for optimization. These responses were measured and used to develop a mathematical model. The NSGA-II, a multi-objective optimization algorithm, was then applied to search for the optimal combination of process parameters that simultaneously maximizes the material removal rate and minimizes the electrode wear rate and surface roughness. The algorithm generated and evolved a set of Pareto-optimal solutions, providing a trade-off between conflicting objectives. The results of the optimization process were analyzed to identify the optimal process parameters that lead to improved machining performance. The study revealed optimal Wire Electrical Discharge Machining (WEDM) parameters for Al6061/Mg/MoS2 composites using NSGA-II. The optimized parameters, including a pulse-on time (Ton) of 105 µs, servo voltage (SV) of 35 V, and peak current (PC) of 31 A, resulted in a Material Removal Rate (MRR) of 7.51 mm3/min and a surface roughness (SR) of 1.97 µm. This represents a 15% improvement in the MRR and a 20% reduction in the SR compared to non-optimized settings, demonstrating the efficiency of the BBD-NSGA-II approach. [ABSTRACT FROM AUTHOR]

In this study, the effectiveness of different wire feed rates, pulsed current, spark gap voltage, pulse on time, and pulse off time was investigated to determine their impact on kerf width. The ideal parameters for wire-EDM machining of aluminum hybrid ceramic composite were determined through experimental investigation and an adaptive neuro-fuzzy inference system (ANFIS). Additionally, five distinct predictive models for influential kerf width parameters were developed as an innovative approach. A hybrid learning methodology combining back propagation and least square estimations was employed to create these predictive models. The prediction ranked the machining parameters affecting kerf width dimensions as wire feed rate, pulsed current, pulse on time, pulse off time, and spark gap voltage. Experimental findings showed that the kerf width of the machined workpiece significantly increased as the wire feed rate increased. This exploratory study suggested a wire feed rate setting of 3 mm/min with a current of 2 A and a pulse on time of 0.6 μs to achieve the best quality machined surface for the aluminum hybrid ceramic composite. Similarly, the proposed optimization model results proved that the experimental findings were near-optimal solutions. [ABSTRACT FROM AUTHOR]

Aluminum–Bronze alloys (Al-10%–Cu-balance) are difficult-to-machine cut alloys. Copper (Cu) metal itself is not suitable for machining. The machining performance of the Aluminum–Bronze alloy sample was investigated by the Wire Electric Discharge Machining (WEDM) method, which is among the non-traditional manufacturing methods used in conductive materials that are difficult to process. The aluminum–bronze sample with a diameter of 20 mm was cut with 0.18 mm molybdenum wire electrode. Table feedrate, pulse-on-time and pulse-space were used as experimental parameters. Surface roughness and energy consumption values were measured in WEDM process. According to Taguchi analysis and ANOVA results, it was determined that the pulse-on-time parameter was effective on the surface roughness and the table feedrate parameter was effective on the energy consumption. [ABSTRACT FROM AUTHOR]

The stainless steel 304 (SS304) and Grade 9 Titanium (3% Al-2.5% V) alloys have excellent resistance to corrosion, formability and weldability and are used in aviation, automobile, medical, etc. But conventional machining of these two superalloys is challenging and hence alternate, unconventional machining is the suitable method to machine these materials, and the wire electrical discharge machining (WEDM) process is the most versatile process. To machine these superalloys effectively, proper selection of WEDM parameters is necessary to enhance the machinability of these alloys. Hence, in the current work, the effect of selected WEDM parameters like current, voltage, wire tension and rate of feed on material removal rate (MRR), surface roughness (Ra), kerf, microhardness (HV) of the machined surfaces and job's final job dimension was examined for the comparative machinability analysis of these two materials. The experiments were conducted using 4 factors with 3 levels as per the L9 Taguchi's array, and from the results, the MRR varied from 7.7 to 25.6 mm3/min for SS304 and 11.6-32.9 mm3/min for Ti alloy. The Ra value varied from 2.132 to 3.236 µm and 2.388 to 3.054 µm for SS304 and Ti alloy, respectively. The hardness varies from 376 to 392 HV and 347 to 361 HV for SS304 and Ti alloy respectively. To improve the machinability of both metals, the input parameters were optimized accordingly. From the comparative machining studies, it was found that the Ti alloy showed better machinability than SS304 in terms of 24.4% higher MRR and 6.4% lower HV variation. At the same time, Ti alloy showed a higher 13.7% 'Ra,' 17.5% kerf, and 0.2% final dimension than SS304 at optimum WEDM conditions. The microstructure of the machined surfaces was examined using SEM images and a 3D profilometer to understand the variation of the surface finish. [ABSTRACT FROM AUTHOR]

Machining thicker workpieces in the process of Wire Electrical Discharge Machining (WEDM) can result in a concave phenomenon known as a "drum shape error" due to the vibration of wires and accumulation of debris, which leads to secondary discharge in the middle of the workpiece. Reducing the drum shape error typically requires a longer finishing process. Finding a balance between precision and machining time efficiency has become a challenge for modern machining shops. This study employed experimental analysis to investigate the effect of individual parameters on the shape error and machining removal rate (MRR). Key influential parameters, including open voltage (OV), pulse ON time (ON), pulse OFF time (OFF), and servo voltage (SV), were chosen for data collection using full factorial and Taguchi orthogonal arrays. Regression analysis was conducted to establish multiple regression equations. These equations were used to develop optimization rules, and subsequently, a user-friendly human–machine interface was developed using C# based on these optimization rules to create a shape error and MRR optimization system. The system can predict the optimal parameter combinations to minimize the shape error and increase the MRR. The results of the verification experiments showed that the prediction accuracy can reach 94.7% for shape error and 99.2% for MRR. Additionally, the shape error can be minimized by up to 40%. [ABSTRACT FROM AUTHOR]

The mechanical characteristics of the aluminium alloy AA 7075, such as its increased ductility and lower fatigue, are well recognized. It is frequently employed in the aerospace sector and is a strong candidate for numerous other technical uses. It is the best option for a variety of applications thanks to its outstanding corrosion resistance. With the help of conventional machining, it is difficult to make complex shaped components. For avoiding these kind of issues, numerous advanced machining methods have been developed. Wire electrical discharge machining (WEDM) is one of them which is the variant of Electrical Discharge Machine (EDM). In this present investigation, an endeavor has been taken to analyze the Wire Electrical Discharge Machining (WEDM) of AA 7075 aluminium alloy with the help of Taguchi's approach. The study analyzed the various process variables that affect the WEDM process. The results were then analyzed to determine the overall performance of the process. Various performance measures namely material removal rate, surface roughness and tolerance errors were considered in this investigation. ANOVA is the statistical analysis performed to determine the significance of process variables. A hybrid grey-based Artificial Intelligence ANFIS model was used to predict the desired multi performance index. The outcomes of the analysis proved that the model offers effective and precise prediction which will be much helpful for the manufacturer to predict the desired performance measures. [ABSTRACT FROM AUTHOR]

This study investigates the optimization of wire electrical discharge machining (WEDM) parameters for microchannel machining of aluminum alloy Al 6061 with improved mechanical properties, which is crucial for various industries. This investigation for microchannel fabrication considers four response parameters: material removal rate (MRR), surface roughness (SR), tool wear rate (TWR), and spark gap (SG), alongside four input parameters: pulse on time (Ton), sparking gap voltage (SGV), wire tension (WT), and wire feed rate (WFR). The selected levels for the experiment are, Ton 105, 115, and 125μs, SGV 10, 25, and 40 volts, WT 6, 8, and 12kgf, and the WFR 2, 4, and 6m/min. By examining Ton, SGV, WT, and WFR, the research identifies optimal conditions using Taguchi-based grey relational analysis (GRA). The findings highlight the importance of parameters such as Ton of 105μs, SGV of 40 volts, WT of 8kgf, and WFR of 4m/min for machining Al 6061-based microchannels, offering valuable insights for future manufacturing endeavors. This research also incorporates the morphology study of machined Aluminium alloy microchannel. [ABSTRACT FROM AUTHOR]

SiC particle reinforced aluminum matrix composites (SiCp/Al) are widely used in aviation, weaponry, and automobiles because of their excellent service performance. Wire electrical discharge machining (WEDM) regardless of workpiece hardness has become an alternative method for processing SiCp/Al composites. In this paper, the temperature distribution and the discharge crater size of the SiCp/Al composite are simulated by a thermophysical model during a single-pulse discharge process (SPDP) based on the random distribution of SiC particles. The material removal mechanism of the SiCp/Al composite during the multi-pulse discharge process (MPDP) is revealed, and the surface roughness (Ra) of the SiCp/Al composite is predicted during the MPDP. The thermophysical model simulation results during the MPDP and experimental characterization data indicate that the removal mechanism of SiCp/Al composite material consists of the melting and vaporization of the aluminum matrix, as well as the heat decomposition and shedding of silicon carbide particles. Pulse-on time (Ton), pulse-off time (Toff), and servo voltage (SV) have a great influence on surface roughness. The Ra increases with an increase in Ton and SV, but decreases slightly with an increase in Toff. Moreover, compared with experimental data, the relative error of Ra calculated from the thermophysical model is 0.47–7.54%. This means that the developed thermophysical model has a good application and promotion value for the WEDM of metal matrix composite material. [ABSTRACT FROM AUTHOR]

Wire Electrical Discharge Machining (WEDM) technology represents an unconventional but vital manufacturing technology in many different industrial branches. The automotive industry and its many significant requirements bring the need to manufacture inserts and mould segments for plastic injections from Albromet W130 material, with a required roughness, Ra, from 4.5 to 5 µm so that subsequent profile etching can be eliminated. A planned experiment of 60 rounds was carried out to discover the optimal machining parameters, namely, the pulse-off time, gap voltage, discharge current, pulse-on time, and wire speed in order for the thickness of 10 to 100 mm (after 10 mm) to demonstrate the required roughness. The goal was to evaluate the surface roughness, maximise the cutting speed, and manufacture it without surface or subsurface defects. The evaluation of the planned experiment led to the establishment of optimised WEDM machining parameters with which thicknesses of 10–100 mm will always be produced with the required roughness, Ra, from 4.5 to 5 µm and with the highest possible cutting speed. It was also proven that the machining does not lead to surface or subsurface defects, and thus, the service life of the manufactured parts will not be affected. [ABSTRACT FROM AUTHOR]

Wire-electrical discharge machining (wire-EDM) is gaining wider acceptance for producing components of Al-matrix composites (Al-MCs) that are hard to machine by traditional methodologies. The related research is primarily limited to ex-situ Al-MCs commonly reinforced with ceramic particles; however, Al-MCs reinforced with in-situ ordered intermetallics have evolved as superior composites nowadays. This research has focused on wire-EDM of in-situ Al/Al3Fe composites developed by the reactive stir-casting route. The influence of three machining variables (pulse-on-time, servo voltage, and peak-current) and one material parameter (vol% of reinforcement) have been studied following the L27 Taguchi design. The integrity of the machined surface has been characterized via measurements of surface roughness (SR) and the alteration of surface chemistry (ASC, ΣCu + Zn + O), in addition to the evaluation of kerf width (KW) as a machining performance indicator. It has been established that all four control factors are significant for KW, while ASC is influenced by all factors except vol% of reinforcement; however, only pulse-on-time is substantial for SR. Analytical models of individual responses are developed while the desirability approach helps to accomplish the multi-response optimization; several confirmation experiments establish the authenticity of these predictions with an error < 8%. Characterizations of machined surfaces and wire electrodes by FESEM and EDS techniques reveal that the surface integrity of in-situ Al/Al3Fe composites varies significantly with machining conditions. [ABSTRACT FROM AUTHOR]

This article presents an experimental investigation of the WEDM (Wire Electrical Discharge Machining) performance of Al-TiB2 composites fabricated using ultrasonic vibration-assisted stir casting and containing four different weight percentages (1%, 2.5%, 4%, and 5.5%) of TiB2 particles. Key machining parameters, namely pulse-on time, wire feed rate, and pulse-off time, are varied at three levels suitable for machining aluminium base material while minimizing wire breakage. Cutting speed, material removal rate, and kerf width are observed individually for each selected level of these process parameters. Surface features are assessed using SEM (Scanning Electron Microscope), EDAX (Energy Dispersive X-ray Spectroscopy), 3D optical surface profilometer, and optical microscopy. Notably, the roughness values are lower in the 4% and 5.5% TiB2 composites compared to the base matrix. This reduction in roughness is due to the protective role of the particles, which shield the surface from melting during the WEDM process. Melting and re-welding phenomena were observed throughout the machining process. It is observed that higher pulse-on time generates harsh sparks, leading to rougher surfaces that include melted zones and pits. The WEDM operations performed on the 5.5 wt% reinforced composite surface result in a significant reduction in roughness, decreasing from around 5 µm to approximately 2.7 µm. [ABSTRACT FROM AUTHOR]

Because of its excellent mechanical qualities and weldability, titanium alloy is used in many different biomedical applications. Wire electrical discharge machining may be used to machine materials with such greater strengths and intricate forms. Using Taguchi-data envelopment analysis-based ranking (DEAR) approach and zinc-diffused coated brass wire electrode to improve Titanium alloy machining was the goal of this research project. The quality metrics that were taken into consideration were surface roughness, kerf width, and material removal rate. Among the selected factors, with an error of 2.7%, the optimal configuration of input factors was determined to be 130 µs (Ton), 40 µs (Toff), 50 V (SV), 6 A (IP), and 8 kg (WT). Due to its relevance in the process of deionization, the Ton is the highest influential parameter for creating quality measurements. [ABSTRACT FROM AUTHOR]

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Wire Electric Discharge Machining (WEDM) is an unconventional machining technology that uses electrical impulses to generate very high temperatures to cut material. The WEDM process hence causes some unfortunate defects, such as cracks and burnt cavities, which can impact the correct functionality of the machined pieces and shorten their service life. This study was carried out to understand which materials remain defect-free after WEDM. The examined materials were the Ampcoloy 35 copper alloy, the high-entropy steels FeCoCrMnNi and FeCoCrMnNiC0.2, and the B1914 and Nimonic 263 nickel alloys. The influence of the machining parameters, namely the pulse off time, gap voltage, discharge current, pulse on time, and wire feed, on the cutting speed and the surface topography of the machined piece was investigated. The surface morphology, the state of the subsurface layer in a cross-section, and the number of diffused elements from the wire electrode were analysed. All the analysed materials were found completely suitable for WEDM machining as they do not form any surface or subsurface defects. [ABSTRACT FROM AUTHOR]

The unconventional wire electrical discharge machining (WEDM) technology represents a vital manufacturing technology in different industrial branches, such as aviation, military, automotive or energy industry. The WEDM energy demand is considerable and it is, therefore, desirable to reduce the machining time by optimising the machining parameters. In the study, the chosen parameters were Pulse off time, Gap voltage, Discharge current, Pulse on time, and Wire feed. Another factor we investigated in our Box-Behnken design of the experiment was the workpiece thickness. The cutting speed, topography, and surface morphology were analysed in the samples produced for the design of the experiment. This investigation was carried out using electron microscopy. The chemical composition of individual spots was analysed as well. The samples were found not to have significant differences in the appearance of craters on the edge and in the centre. Similarly, there was no significant difference observed between thicknesses and different parameter settings. The surfaces also show a large number of small bubbles. There were, however, no cracks or other defects found, even in the cross-sections of all samples. [ABSTRACT FROM AUTHOR]

Wire electrical discharge machining (WEDM) is utilized to cut sophisticated curves or shapes that would be challenging to cut using traditional techniques. The challenge lies in simultaneously optimizing multiple conflicting objectives, such as maximizing material removal rate (MRR) while minimizing surface roughness (SR) and kerf width, to achieve high-quality machining results. This study addresses this challenge by introducing a multi-objective optimization approach using the Taguchi method and the Design of Experiments (DOE) to optimize WEDM parameters. The WEDM model AQ327L cut a workpiece material from stainless steel AISI 304 using a 0.25-mm brass wire electrode diameter. The variable input parameters were a pulse on time (Ton), a pulse of time (Toff), and a peak current (IP). The average of means analysis (ANOM), analysis of variance (ANOVA), and single-to-noise (S/N) ratio were used to determine the effect of WEDM parameters on the responses. The multi-objectives optimization introduced the ideal setting parameters were a combination of 11.33 μs Ton, 24 μs Toff, and 11 A IP. ANOVA and ANOM demonstrated that the Ton followed by IP are the most influential factors in the MRR and kerf width. In contrast, the Ton followed by the Toff are the most influential factors in SR. Finally, the findings demonstrated that the multi-objective optimization by the Taguchi approach could increase the quality of the WEDM process of AISI 304. [ABSTRACT FROM AUTHOR]

The Wire Electrical Discharge Machining (WEDM) process is an accurate method for manufacturing high-added-value components for industry. Continuous developments in the process have resulted in specialized machines used in sectors such as aerospace and biomedical engineering. However, some fundamental aspects of the discharge process remain unresolved. This work aims to study the influence of discharge location and bubble expansion on the occurrence of subsequent discharges. A high-speed video camera observation system was constructed to capture images of each discharge. From the acquired images, an algorithm was devised to determine the discharge location based on grayscale analysis. Moreover, the voltage and current waveforms of the discharges and the framing signals of the high-speed video camera were then obtained using an oscilloscope. Synchronizing the observation images and signals allowed for calculating the delay time for each single discharge. The results indicate that most of the discharges occurred near the boundary of the bubble and during bubble expansion. This finding has been observed for a variety of machining conditions and can be explained by the effect of the debris particles concentrated at the bubble boundary. This study provides useful information for better understanding the discharge process in WEDM. [ABSTRACT FROM AUTHOR]

In wire electrical discharge machining (WEDM), cutting efficiency is a significant process index whose improvement has always been the research focus. Among the many factors affecting cutting efficiency, discharge energy is the most important factor. Different energy distribution form pulses were obtained by changing the peak currents at single-pulse different discharge stages. Through single-pulse discharge experiments, pulse energy distribution how to impact discharge channel motion characteristics was studied. When the energy distribution is changed through gradually increasing the peak current, an outward-pointing pressure difference will be formed inside the channel, which provides a driving force for the channel to move faster, accelerating the material erosion rate and increasing the discharge crater surface size. The cutting results reveal consistent variations in the cutting efficiency and surface size of individual discharge crater with the pulse energy distribution form. Through changing single-pulse energy distribution, the cutting efficiency can be improved by about 21%. [ABSTRACT FROM AUTHOR]

When utilising traditional machining processes, convincing and competent processing with ultra precision of superalloys are highly difficult and stiff task. Accordingly, the authors recognised a need for non-conventional machining (NCM) for processing of alloy 718 (other name 'Inconel 718' or UNS N07718) using wire electric discharge machining (WEDM). L16 Taguchi's orthogonal array has been utilised for preferred design of experiment. Pulse on duration (Ton), pulse off duration (Toff), wire speed (Uw), and current (I) has been selected as control factors to study the effects of performance. Material removal rate (MRR), Kerf Width (KW) and Surface Roughness (SR) has been assessed as an output performance. Analysis of variance (ANOVA) is also performed and found that I has the greatest influence on MRR while Uw is lowest, with contribution of 47.11 % and 6.05 % respectively. For KW, Toff is greatest influential factor while I is lowest, with contribution of 35.39 % and 4.35 %. For SR, Ton is greatest influential factor while Toff is lowest, with contribution 87.8 % and 3.27 %. Also error between the actual and predicted values is below 5 %. For MRR, the error is 4.20 % while for KW and SR, it is 0.31 % and 2.21 % indicating close alignment with the achieved value. [ABSTRACT FROM AUTHOR]

Armour steel is a type of steel that is often used in armoured vehicles, military equipment, and structural components that require a high level of resistance to penetration. Because of its high strength and hardness, cutting armour steel presents various obstacles. To overcome these challenges in armour steel cutting, innovative cutting methods, specialized equipment, and careful process planning are required. The current work discusses an experimental investigation that focuses on input process parameters of wire electrical discharge machining and on multi-objective optimization to obtain the best cutting rate (CR), surface roughness (SR), wire electrode temperature (TE) and material removal rate (MRR) for armour steel. The fractional factorial approach has been used in the investigation, with pulse off time (B), pulse on time (A), spark voltage (D), peak current (C), wire feed (E) as machining parameters and workpiece thickness (F) as a material parameter. The main and interaction impacts of the input parameters on the response parameters have been examined using the main effect plot, interaction plot, and ANOVA analysis, followed by the development of regression modeling. The research revealed that the pulse on time and workpiece thickness have the most significant contributions to CR and SR, with 55.25% and 21.77% contributions for CR and 67.87% and 8.72% contributions for SR, respectively. Toff and spark voltage are the major contributors for TE with 33.58% and 26.30% respectively and Ton is a major contributor with 70.04% for MRR. The ideal input parameters for CR [0.71 (mm/min)], SR [2.46 (microns)], TE [52 (°C)] and MRR [23.85 (mm3/min)] have been found to be A2B1C2D1E1F1, A1B2C2D2E1F2, A1B2C1D1E1F2 and A1B2C1D1E2F1 respectively. The modified crow search algorithm (MCSA) has been used in this study for single and multi-objective optimization, and their results contrast with other methods such as Rao-1 and Shuffled Frog Leaping Algorithm (SFLA). According to the conclusions of the present investigation, this study demonstrates that the MCSA technique exceeds the Rao-1 and SFLA techniques in terms of producing globally optimal outcomes for the specific problem under examination. [ABSTRACT FROM AUTHOR]

The wire-electrical discharge machining (wire-EDM) is increasingly recommended for the machining of complex-shaped components with high surface finish and geometrical accuracy, specifically for difficult-to-machine advanced materials like Al-matrix composite (Al-MCs). The related research is primarily restricted to ex-situ Al-MCs, although in-situ ordered intermetallics reinforced Al-MCs are receiving growing attention due to their superior comprehensive mechanical properties. The present work deals with an Al-2Mg/20 vol.% in-situ Al3Fe composite manufactured by the reactive stir-casting method and focuses on its machining by wire-EDM via experimental and computational approaches. Experiments have been conducted following the response surface method (RSM) considering four process variables, namely, pulse-on time (TON), servo voltage (SV), peak current (IP) and wire feed rate (WFR). The integrity of the machined surfaces has been characterized by evaluating the change in surface chemistry (CSC) and surface roughness (SR), while the material removal rate (MRR) has been determined as the machining performance index. Analysis of variance (ANOVA) and RSM-based mathematical models reveal that TON is the most influencing parameter, and it raises MRR and SR but reduces CSC considerably. The optimization of machining conditions has been performed by metaheuristic approaches, namely, Teaching and Learning-based optimization (TLBO) and Artificial Bee Colony (ABC) apart from multi-objective RSM (MORSM) based on the trade-off analysis. The performances of TLBO and ABC techniques are found to be identical and provide much greater MRR at the cost of diminished surface integrity, i.e., higher SR and CSC, when compared with the MORSM technique. The robustness of the developed models has been validated by confirmatory experiments with a calculated overall error of ≤ ± 8%. Finally, the surface integrity aspects are reaffirmed and correlated with input variables through detailed characterizations of the machining surfaces by FESEM-EDS. [ABSTRACT FROM AUTHOR]

Wire-breakage (WB) during Wire electric discharge machine (WEDM) is a critical issue since it halts the machining process and leads to increased energy consumption, lower productivity, and diminished product quality. Current study applies machine learning-based classification approaches: logistic regression, random forest, decision tree, and Gaussian Naïve Bayes for prediction of wire-breakage instances during WEDM of nimonic 263 executed under varying cutting conditions of peak current (IP), spark-gap voltage (SV), pulse-on time (Ton) and pulse-off time (Toff). The decision tree and Gaussian Naïve Bayes' accuracy have equal accuracy (96%), whereas the logistic regression has a comparatively lesser accuracy (92%). Random forest has the highest accuracy of a hundred percent for the testing data. This research demonstrates that binomial classification algorithms may be employed offline to anticipate input parameters contributing to wire breaking. Avoiding the parametric combination leading to wire breakage during machining may enhance productivity and improve product quality. [ABSTRACT FROM AUTHOR]

10CrNi3Mo alloy steel has the characteristics of high hardness and wear resistance, and is widely used in aircraft and spacecraft, shipbuilding and so on. However, its conventional processing method has high tool loss. Wire Electrical Discharge Machining (WEDM) technology is based on electrode pulse discharge to corrode materials. There is no direct contact between the tool and the workpiece, so it is suitable for processing materials with complex shapes, such as high hardness and high brittleness. The focus of this study is to investigate the effects of different electrical parameters such as pulse width, pulse gap, current, and wire feeding speed on the recast layer thickness (RCL) and surface roughness (SR) of 10CrNi3Mo alloy steel processed by wire discharge machining using orthogonal experiments. The gray correlation method was used to optimize the above two process indicators, and seeking optimal processing parameters. The optimized recast layer thickness was 8.65 μ m. The surface roughness is 1.932 μ m. Achieve expected goals. [ABSTRACT FROM AUTHOR]

IntroductionWire-electric discharge machining (WEDM) possesses multiple benefits over traditional production approaches; it allows for the precise processing of complex and rigid particulate-reinforced composite materials. Aluminium alloys have found widespread applications in surgical components, shipbuilding, aircraft, automobiles, and inhaling gas cylinders for scuba diving, due to its good strength, and light weight properties.MethodsThe main aim of this investigation is to optimize different process variables for LM6/B4C/Fly ash particle reinforced hybrid composites using WEDM to attain performance metrics such as maximum material removal rate (MRR) and minimal surface roughness (SR). Taguchi’s L27 orthogonal array (OA) matrix and Grey Relational Analysis (GRA) were used.Results and DiscussionAccording to ANOVA, the two variables with the most significant impact on MRR and SR are gap voltage and reinforcement percentage, with respective impacts of 29.59% and 20.69%. When the composite is machined, the following process variables work best: GV of 30 V, Ton of 10 µs, Toff of 2 µs, WF of 4 m/min, and R of 6%. A low gap voltage causes the erosion to rise and the MRR to increase. However, SR will also increase which is undesirable, so optimum gap voltage values are required for WEDM.

In the present work, the Inconel 625 material is utilized for processing on a wire electrical discharge machine. The zinc-coated brass wire is used as a tool electrode. The Taguchi mixed orthogonal L27 experimental design is developed to perform the experiments. The parameter was induced on normal and cryogenic material such as pulse on time (Ton), pulse off time (Toff), discharge current (Ip), wire feed (Wf), and wire tension (WT). The characteristics responses i.e., material removal rate (MRR), surface roughness (Ra), and overcut (OC) were analyzed. The genetic algorithm (GA) was applied for the evaluation and measuring of fact, which determined its performance, and predicted facts were considered for particle swarm optimization (PSO) technique multiple objective problems. After the comparison, the facts predicted were analyzed for the response, which revealed the surface integrity and accuracy on the machined surface. The solution implied that applied PSO gives highly significant results on optimal setting parameters of WEDM machining. The 0.419 μm surface roughness has been obtained by a cryogenic process as compared to normal (0.880 μm). The material removal rate for the cryogenic process was found to have decreased in PSO by 21.18 % and in GA by 2.78 % in comparison to the normal process. The obtained results give the utmost measure for the suitability of time reduction and cost-cutting in productivity rate.

The intend of current study was focused on the prediction of material removal rate (MRR) and surface roughness (SR) for the AA7050-SiO2 composite during wire electric erosion or discharge machining (WEDM) process using a brass (Br) wire electrode. Here, stir casting process was employed to develop the AA7050 matrix composite with inclusion of 10wt.% SiO2 particle reinforcement. The multi-objective optimization method of Technique for order preference by similarity to ideal solution (TOPSIS) approach has been applied to find out the optimal setting of input machining parameters such as peak current (Ip), pulse-on time (Ton) and pulse-off time (Toff). Furthermore, the significant effects of parameters were identified by analysis of variance (ANOVA). Taguchi L9 (33) orthogonal design has been formulated to perform the experimental work. TOP SIS results stated that the optimal setting of Ip at 30 amps, Ton of 130 μs and Toff of 55 μs provide the better MRR with lesser SR. The ANOVA results noticed that Ip has the prime noteworthy parameter over the adopted responses having a contribution of 45.67%, followed by Ton (32.34%) and Toff (12.26%), respectively. The confirmation test was carried out by the optimal parameters setting to verify the predicted results. Finally, the scanning electron microscopy (SEM) test was carried out for the machined surface of the composite specimen and it was reveals that the formation of craters and recast layer thickness in the machined surfaces.

Present study is focused on optimization of WEDM process parameters for increased productivity and improved surface quality of the machined surface of hybrid composite [Al6061 (90 %), SiC (2.5 %) and TiB2 (7.5 %)] by utilizing the trim cut strategy. Effects of four factors namely, pulse on time (Ton), peak current (Ip), wire offset (WO) and rough-cut history (RCH) have been investigated on response characteristics namely, material removal rate (MRR), surface roughness (SR) and Recast layer (RL) thickness; using Box-Behnken design (BBD) for the experimentation. Three levels of RCH i.e., high, medium and low have been included to investigate the effectiveness of trim cut strategy for dealing with rough-cut surface under varied conditions. The optimized parametric setting has been obtained for multiple responses using desirability function. RCH is found to be most significant factor for MRR, while pulse on time (Ton) is found most significant for SR and RL. WO has been found to play an important role in controlling the thickness of RL. It is observed that after trim cut, surface roughness is improved for experiments conducted under high and medium levels of RCH. However, almost no improvement in SR is obtained for low level of RCH. Trim cut strategy is also found to be effective in reducing the thickness of recast layer, however, it is noticed that the percentage reduction in recast layer thickness for samples machined under high level RCH is greater than that for the other two levels of RCH.

This study investigates the impact of combined texturing by micromachining and chemical functionalization on the wetting behavior and water condensation on stainless steel 304. The transition from Wenzel to Cassie-Baxter or impregnated Cassie-Baxter regimes is investigated. Understanding this transition is critical for advancing surface engineering, as it enables precise control over wetting behavior for various applications. Herein, we report on the wire EDM (wEDM) machining on stainless steel 304 to produce two distinct microstructure patterns with directional canals or pyramidal structure, and their performance in water condensation. These patterns significantly impact water condensation performance. wEDM is employed to create surface roughness, followed by phosphoric acid treatment and chemical functionalization with trichloro-1H,1H,2H,2H-perfluorooctyl silane. Contact angle measurements reveal a synergistic effect between groove direction and silane coating, leading to hydrophobic surfaces and dropwise water condensation. Specimens with directional canals exhibit a contact angle of 150°, while specimens with pyramidal structures exhibit 151o. Roll-off angle experiments showcased distinct behavior among specimens featuring canals or pyramidal structures. Specimens with canals exhibit notably lower roll-off angles compared to both flat surfaces and those with pyramidal patterns, leading to a dependence of roll-off angles on the orientation of canals. In humid environments, micromachined specimens exhibit superior water condensation capability compared to untreated SS304 surfaces. Chemically functionalized grooved specimens present larger condensate droplet diameters than flat surfaces. An enhancement in water condensation and a sevenfold higher latent heat transfer coefficient is reported. Specimens with chemical functionalization achieve corrosion protection with an efficiency reaching 82.9%. [ABSTRACT FROM AUTHOR]

The relationships between machining conditions, boundary layer and mechanical component functionality are known qualitatively for selected Wire Electrical Discharge Machining (Wire EDM/WEDM) applications and continuous further developments of this manufacturing technology minimize the thermal influences significantly. Nevertheless, the use of WEDM processes has so far been severely limited in safety-critical applications, especially in the field of turbomachinery construction and aerospace. For example, the removal of the generated surface layers is often still mandatory, although cutting processes can also leave a distinct thermo-mechanically influenced rim zone on the component. This conservative approach currently unnecessarily reduces the manufacturing potential of WEDM processes considerably and calls for an objective comparison of component function. In this paper, therefore, the flexural bending fatigue strengths of differently wire-eroded surfaces based on roughing-finishing sequences and optional post-processing treatment are compared with industrially established reference process chains. [ABSTRACT FROM AUTHOR]

The article aims to estimate the importance of machining parameters for the performance measure material removal rate (MRR) in the Wire Electrical Discharge Machining (WEDM) processing of MONEL 400 K. Wire feed, Time On and Time Off (downtime) have been discovered to be more impactful in deciding the MRR criterion substantially. The significant contribution of relevant input parameters varies according to the objective response behaviour of the parameter. The effect of Time off is the inverse of Pulse on Time, and it leads to the increased MRR as Time off increases, but surface roughness decreases. The material was flushed away effectively during higher Time off, leading to good-quality machined components. It endeavoured to recognize the most significant machining factors for experimentation, and the response surface methodology (RSM) strategy tracks down the best arrangement of boundaries for increasing the MRR. Parametric evaluation on WEDM of MONEL 400 K stands new in this study which many researchers fail to explore in detail followed by response surface methodology to analyse the results. The conformity tests were completed to assess the RSM strategy's expected outcome, proving promising. The results confirmed that the increased MRR of 0.06938 gm/min is obtained at the optimal level of pulse On Time of 10 μs, down Time of 2 μs, and wire feed rate of 4 m/min. [ABSTRACT FROM AUTHOR]

AISI P20 tool steel is commonly used for engineering of die holders, rails, plastic molds, wear strips, bolsters, shafts, and backers. When normally heated and sub-cooled, it experiences metallurgical modifications. Because the essential aspect of the "wire-electro discharge machine (WEDM)" is product finishing, this research examines the parametric responses when machining parent metal and sub-cooled metal (AISI P20). Thus, it is always necessary to choose a proper parametric arrangement for reaching maximum material removal rate (MRR), cutting speed with minimum surface roughness (SR), and kerf width. The effects of pulse on time, wire speed, discharge current, wire tension, and flushing pressure on individual machining reactions are also discussed in this study. An orthogonal array was created using Taguchi's mixed experimental approach. The measurement alternatives and ranking according to compromise solution (MARCOS) method, the Honey Badger Algorithm, and the Taguchi-MARCOS method are engaged to obtain the important machining constraints and the optimal parametric settings for each response. When compared to the parent material, sub-cooled material has a greater cutting speed, SR, kerf breadth, and MRR. Here, cutting speed, MRR, and fitness were maximized along with minimization of SR and kerf width using the Honey Badger Algorithm as compared to both the MARCOS and Taguchi-MARCOS methods. According to ANOVA, for both parent and sub-cooled material, discharge current was the most significant and influential factor. The sub-cooled material's machined surface contains smaller deposits and more spherical globules than the parent material, which has bigger melted deposits. [ABSTRACT FROM AUTHOR]

The present study focused on the machinability of Ti-3Al-2.5 V for wire-electrical discharge machining (WEDM) using "BroncoCut-X wire" (zinc-coated copper wire). The machining characteristics have been evaluated by varying wire-tension (Tw), wire-speed (Sw), flushing-pressure (Pf), discharge current (Id), and spark-on-time (Son). The response characteristics associated with cutting-speed (Cs), kerf-width (KW), and surface roughness (RA) have been collected and analyzed using main-effect plots, scanning electron microscope (SEM), and analysis of variance (ANOVA). The maximum Cs and minimum KW and RA are obtained upto 8.90 mm/min, 3.34 µm and 0.2218 mm, respectively. Additionally, the novelty lies in the smart hybrid prediction tool considering the conflicting nature of responses are converted into single responses using Grey Relation Analysis (GRA) and Fuzzy Interference System (FIS) (Namely: Gray-Fuzzy Reasoning Grade (GFRG)). Furthermore, the optimal performance is calculated using Rao-algorithms (i.e., Rao1, Rao2, and Rao3). The obtained ideal machining condition is 16N wire-tension, 3 m/min wire-speed, 8 kg/mm2 flushing-pressure, 21A discharge current, and 14 µs spark-on-time. The result has also been compared with the JAYA-algorithm and improved-grey wolf optimizer (I-GWO) to demonstrate the efficacy of the intended approach. The confirmation test has been conducted and obtained that the GFRG-based results are further improved by using a hybrid GFRG-based Rao-algorithm of 9.55%, 2.36%, and 7.99% as Cs, KW and RA, respectively. Furthermore, this study shows that the proposed multi-objective optimization method not only leads to more stable solutions but also to shorter run times and enhanced quality to support engineers in reducing the cost of item failures. [ABSTRACT FROM AUTHOR]

Wire-cut electrical discharge machining (WEDM) technology is used to cut composite materials. In this work, a hybrid composite of an aluminum matrix material reinforced with boron nitride and molybdenum disulfide (MoS2) was created utilizing the stir casting technique. Its WEDM machinability was investigated. The input parameters for the study are pulse on time (Ton), pulse off time (Toff), wire feed (WF), and wire tension (WT) output parameters material removal rate (MRR) and surface roughness (SR). The tests were designed using L27 orthogonal arrays. The analysis of variance was used to determine the contribution of input process characteristics impacting output performance. The ideal settings were determined using an entropy approach weight combined with the vise kriterijumska optimizacija kompromisno reseneje (VIKOR) method. In this work, the entropy weight criterion for MRR and SR were 0.52 and 0.48, respectively. The best ideal parameters were obtained from the VIKOR evaluation ratings at the (12th) trial, with a Ton of 8 μs, 28 μs of Toff, WF of 7 m/min, WT of 12 g and a higher appraisal grade of 1. A scanning electron microscope was used to analyze the surface morphology of the machined surface. [ABSTRACT FROM AUTHOR]

It is essential to determine the most suitable machining method for magnesite-reinforced Aluminium 6061 composites, which possess excellent mechanical properties, especially notable tensile strength and hardness. The composites were produced using a stir-casting technique, incorporating reinforcements of lightly-calcined magnesite, dead burnt magnesite, and waste magnesite in weight fractions of 2.5%, 5%, and 7.5% within an aluminium 6061 matrix. Wire electrical discharge machining was employed to investigate the machining characteristics of these composites, using controllable process parameters such as cutting speed, pulse-on and pulse-off times, and the weight fraction of magnesites. Two performance indicators such as surface roughness and material removal rate were tested for various parameter combinations by central composite design. To comprehend the impact of the study parameters, contour charts were drawn. MRR increases at a high cutting speed of 2 mm/min when the pulse-on time changes from 120 μs to 125 μs. SR increases when the pulse-on times above 120 μs at all cutting speeds. High cutting speeds make high MRR irrespective of the weight fractions of reinforcement. High pulse-on times make the material melt more, which increases the material removal rate. Because specimen surface material erodes quickly and forms microcracks, high pulse-on time also results in high surface roughness. To optimize the WEDM machining conditions for each composite, hybrid SSO-DF and DFO-DF optimizers were developed by combining the desirability function with Salp-swarm optimization and Dragonfly optimization algorithms. The cutting speed of 2 mm/min and the pulse-on time of 114 μs produce the best performances on the composites. [ABSTRACT FROM AUTHOR]

Recent developments of orthopedic implant applications have discovered a variety of new metallic biomaterials known as β-type titanium alloys. The μ-WEDM (micro-wire electro discharge machining) surface treatment technique, capable of improving the surface properties of orthopedic implants, was studied in a machining Ti-29Nb-13Ta-4.6Zr alloy. This study aimed to evaluate material removal rate (MRR), kerf width, average surface roughness, microhardness and antibacterial response at different machining parameters which are capacitance (1 nF, 10 nF and 100 nF) and gap voltage (80 V, 95 V and 110 V). The Taguchi method was used to optimize the mentioned output parameters, while ANOVA (analysis of variance) described the significance and contribution of capacitance and gap voltage. Grey relation analysis (GRA) was conducted to perform multiple output optimization. For antibacterial response, cultivations of B. subtilis, E. coli, P. aeruginosa and S. aureus bacteria on treated surfaces for 72 h were performed. As the results, optimal values of MRR, kerf width, crater area, average surface roughness and microhardness were equal to 0.0637 mm3/min, 93.0 μm, 21.8 μm2, 0.348 μm and 442 HV, respectively. Meanwhile, μ-WEDM treatment improved antibacterial properties while the highest antibacterial response was achieved at the lowest average surface roughness resulting in least biofilm formation on treated surfaces. [ABSTRACT FROM AUTHOR]

In this paper, a strategy has been set for minimizing the corner error in the modification of pulse and non-pulse parameters. Taguchi's philosophy has been used to design the experiment by varying process parameters (i.e. Spark-on Time (STon), Wire Tension (WT), Servo-Voltage (Sv), Discharge Current (DC) and Wire-speed (Sw)), to explore the machining outcomes. The response characteristics have been measured in terms of cutting speed (Cs), Corner Error (CD) and surface Roughness (RA) using Topas plus X wire of ϕ 0.25 mm diameter. The machining performance characteristics were analyzed using main effect plots and analysis of variance (ANOVA). Furthermore, a soft computing-based hybrid optimization technique (Artifical Neural Network (ANN)-based Multi-Objective Grey Wolf Optimizer (MOGWO)) has been utilized to search the multi-optimum parameter setting for superior machining results. The most significant parameter observed is DC for Cs, which is determined to be 34.81%. Moreover, WT found 26.29% and 34.10% for CD and RA, respectively. The confirmation test shows that the maximum absolute percentage errors are observed as 3.89%, 6.3% and 9.7% for Cs, CD and RA, respectively. The proposed hybrid technique can generate superior solutions compared to the existing algorithms. Notably, the outcomes obtained on new instances exhibit potential, purposeful, and efficacy. [ABSTRACT FROM AUTHOR]

Improving energy efficiency in manufacturing processes is a critical global concern for the industry. Manufacturers strive to enhance energy efficiency across all manufacturing operations to remain competitive globally, aiming to reduce production times without compromising product quality. While there has been significant research characterizing energy efficiency and surface roughness in conventional processes like turning or milling, studies on unconventional manufacturing techniques are limited. This study focuses on optimizing a wire electrical discharge machining (WEDM) process to minimize energy consumption while maintaining surface roughness. Various cutting parameters, such as pulse on-time, pulse off-time, servo voltage, wire tension, wire speed, and wire voltage, were evaluated. Experiments were conducted using Taguchi's methodology with a L 27 orthogonal array, employing AISI D2 steel plates of 19 mm and 25 mm thickness as the machining material. The research identified that optimal parameters for reducing energy consumption and improving surface roughness included a pulse on-time of 10 s, pulse off-time of 11 s, servo voltage of 44 V, wire tension of 50 g-force, wire speed of 7 m per minute, and wire voltage of 9 volts. This combination led to an 8% reduction in energy consumption and a 1% enhancement in surface roughness compared to baseline values. [ABSTRACT FROM AUTHOR]

Deriving inspiration from natural hierarchical superhydrophobic surfaces, multi-scale structures were manufactured on AA6082 surfaces via wire electrical discharge machining (WEDM), featuring microscale texture due to spark erosion, superimposed upon a wide-range simple and more complicated geometries of submillimeter profiles. The effect that the higher-order scale morphologies had on wettability was investigated. The dual-scale morphology elevated the hydrophobicity of the surfaces compared to single-scale or unmodified surfaces, reaching superhydrophobicity (151°) in the case of a certain triangular profile. Rectangular and triangular profiles facilitated the higher contact angles, while re-entrant geometries were able to totally prevent cavity wetting. A correlation of static contact angle with roughness parameters of the larger scale such as Ra, Rz, Rp, Rsk, and Rku for certain geometry configurations was identified. Peak hydrophobicity resulted at Ra = 70 μm, Rz = 240 μm, and Rp = 160 μm concerning simple geometries. Negative Rsk and Rku > 1.5 affected negatively contact angle of samples. All investigated tested types were found to reach higher hydrophobicity at moderate drop volumes (5 μl). The fabricated samples were anisotropic in at least two directions, showing decreased hydrophobicity in the front, parallel to the groove direction. When tested in multi-directional dynamic tilting up to 90°, the more complicated geometries were able to retain resistance to spreading. All samples demonstrated superliquiphilicity with lower surface tension liquids, making them strong candidate in applications such as oil/water separation. Finally, all samples tested sustained their hydrophobic character subsequent to a 3-month atmospheric exposure period. [ABSTRACT FROM AUTHOR]

Wire electric-discharge machining (WEDM) is the most desirable material processing technique for making complex designs, especially in hard-to-machine conductive materials with high fidelity and accuracy. Current study aims to streamline the WEDM parameters to process Inconel 690. Experimental trials are effectuated using Box-Behnken design of response surface methodology. Processing conditions of parameters are varied to scrutinize the performance of the technique. Federated mode of analysis of variance and grey relational analysis (GRA) are implemented to the study the significance and streamlining of the parameters respectively, to attain increasing material removal rate and small surface roughness for inconel 690 which is highly preferred for nuclear reactor and gas turbine industry. After applying GRA technique, streamlined condition of parameters is found which gives results with acceptable error. Surface topography of the post processed workpiece is also anatomize using scanning electron microscopy. [ABSTRACT FROM AUTHOR]

Present study is focused on optimization of WEDM process parameters for increased productivity and improved surface quality of the machined surface of hybrid composite [Al6061 (90 %), SiC (2.5 %) and TiB2 (7.5 %)] by utilizing the trim cut strategy. Effects of four factors namely, pulse on time (Ton), peak current (Ip), wire offset (WO) and rough-cut history (RCH) have been investigated on response characteristics namely, material removal rate (MRR), surface roughness (SR) and Recast layer (RL) thickness; using Box-Behnken design (BBD) for the experimentation. Three levels of RCH i.e., high, medium and low have been included to investigate the effectiveness of trim cut strategy for dealing with rough-cut surface under varied conditions. The optimized parametric setting has been obtained for multiple responses using desirability function. RCH is found to be most significant factor for MRR, while pulse on time (Ton) is found most significant for SR and RL. WO has been found to play an important role in controlling the thickness of RL. It is observed that after trim cut, surface roughness is improved for experiments conducted under high and medium levels of RCH. However, almost no improvement in SR is obtained for low level of RCH. Trim cut strategy is also found to be effective in reducing the thickness of recast layer, however, it is noticed that the percentage reduction in recast layer thickness for samples machined under high level RCH is greater than that for the other two levels of RCH. [ABSTRACT FROM AUTHOR]

In the field of machining different grades of alloys using wire electrical discharge machining (WEDM), developing efficient techniques has been a challenge. Typically, specific supervised learning and optimization (SLO) methods are created for individual alloys, resulting in a time-consuming process. To address this issue, a unified SLO approach capable of handling various grades of alloys with different compositions and physical characteristics is proposed. In this study, three stochastic optimization tools are combined with a multi-layer neural network to determine the optimal SLO strategy. Five different alloy grades are considered, with inputs consisting of six variables, including chemical composition, and physical properties. The neural network architecture used is 19-500-500-4, and it is combined with a gray wolf stochastic algorithm, proving to be the most effective SLO methodology. The results indicate that regardless of the alloy grade, the pulse on time significantly affects the material removal rate, kerf width, and thickness of the recast layer (RL). Surface roughness is primarily influenced by alloy properties such as density, specific heat, and elements like Cr, Mo, and Ni. Additionally, the recast layer is dependent on factors such as V, Ti, thermal conductivity, and thermal diffusivity of the materials. Validation experiments demonstrate that the mean squared error of all responses for each alloy remains within 5.0%. This unified SLO approach provides a promising solution for optimizing the machining process of different alloy grades, reducing the need for separate techniques for each material. [ABSTRACT FROM AUTHOR]