Unconventional Machining Processes Research Articles

An experimental investigation of abrasive jet machining parameters for optimized surface finish of mild steel components

Abrasive jet machining is one of the unconventional machining processes that are initiated for alternations of surface characteristics of ductile materials, like mild steel, due to the entrainment of high-velocity abrasive particles. The present experimental investigation deals with the major process parameters of the AJM process, namely air pressure, standoff distance, and time of machining, on the average surface roughness (Ra) of mild steel specimens. Experiments were conducted on the self-developed AJM setup using aluminum oxide abrasive particles of an average size of 50 µm. The pressure of air is changed in three levels, 6, 7, and 8 bars. The standoff distance is taken as 2 mm constant for all the cases. The surface roughness was measured at machining times of 20, 40, and 45 seconds. The presence of the increase of air pressure from 6 to 8 bars applied for all the machining time showed an increasing influence on roughness, although always significant in Ra. For 8 bars of pressure and 45 s of machining, the minimum resulted in 1.39 µm, compared with 3.47-4.02 µm. The rate of decrease in surface roughness is sharp with increasing machining time from 20 to 40 seconds but marginal beyond that. An optimal machining time of 40–45 seconds was identified to obtain a minimum Ra. Capability of AJM as an effective technique to enhance the surface finish of mild steel components, and practical insight of this study is very useful toward optimization of process parameters for attaining the targeted surface quality. The results obtained may assist in expanding the industrial application of AJM toward the finishing of ductile materials in various manufacturing fields.

Optimization of process parameters in micro electrochemical machining using TOPSIS technique with Analytical Hierarchy Process (AHP)

Electro-chemical machining (ECM) is one of the extensively used unconventional machining processes employed in industries to machine difficult-to-machine materials such as super alloys, titanium alloys, stainless steel, etc It does not impart any mechanical stresses on the workpiece. The primary requirement of the work material used in this process should be electrically conductive materials. In favour of these characteristics, Hastelloy C276 is used as a work material because it exhibits excellent physical properties over cast iron. Generally, the quality of machining mostly relies on the electrolyte (mmol L−1), feed rate (mm/rev), and duty ratio. These credential parameters are considered in this present work to enhance the machining quality, such as circularity, taper angle, and metal removal rate (MRR). The Taguchi L9 orthogonal array is used to learn machining behaviour under various circumstances. And this time, an Analytic Hierarchy Process (AHP) is used to allocate the weight for each response in the TOPSIS multi-criteria decision-making method. According to the findings, sodium nitrate (NaNo3) has a higher metal removal rate than sodium chloride (NaCl) and sodium bromide (NaBr). It will, however, result in a low-quality hole. The taper angle is inversely proportional to the feed rate.

Parametric Study of Electrical Discharge Turning Process of Al7075/ZrO2-MMC

The mechanical properties of Aluminum metal matrix composites (AMMCs) have made them a popular choice in various industries such as automotive, aerospace, and marine. However, their composition, which includes abrasive reinforcements, makes them difficult to machine using conventional techniques. So, unconventional machining processes play a vital role in the machining of these materials. Electrical discharge turning (EDT) is one of the configurations of electrical discharge machining (EDM) that is utilized to machine cylindrical-shaped workpieces. In this study, AMMC Al 7075/ZrO2 was fabricated using the stir casting method. Further, investigated the effect of machining parameters of EDT, namely pulse Current (I), pulse on time (T-ON), and rotating speed (RPM), on Al 7075/ZrO2 in terms of material removal rate (MRR), tool wear rate (TWR), and overcut (OC) using one parameter at a time (OPAT) method. The outcome of the experiment reveals that MRR, TWR, and OC are more impacted by pulse current than by rotational speed. A decrease in TWR was also found with an increase in pulse on time for all rotational speeds. The size of the craters and globules observed lower with 1400 RPM in the micrograph image.

Comparative study on manufacturing of EDM electrodes by laser sintering process

The abstract aims to investigate the comparative performance of Electrical Discharge Machining (EDM) and Selective Laser Sintering (SLS) with unconventional machining processes. Unconventional machining processes have gained significant attention due to their versatility and capability to fabricate intricate components with high precision. This study focuses on assessing the efficacy of EDM and SLS techniques in terms of data removal rate and relative wear volume. Electrical Discharge Machining (EDM) is a thermal erosion process that utilizes electrical discharges to remove material from a workpiece. In contrast, Selective Laser Sintering (SLS) is an additive manufacturing technique that employs a laser to selectively fuse powdered material, layer by layer, to build up a three-dimensional object. Both methods offer unique advantages in terms of precision, speed, and material compatibility. The performance evaluation of these techniques involves analyzing key parameters such as data removal rate, which measures the volume of material removed per unit time, and relative wear volume, which quantifies the wear on the tool or workpiece during the machining process. By comparing these metrics, insights into the efficiency and effectiveness of EDM and SLS can be gained, aiding manufacturers and researchers in selecting the most suitable method for specific applications. Through experimental investigations and data analysis, this study aims to provide valuable insights into the capabilities and limitations of EDM and SLS in unconventional machining processes. The findings will contribute to advancing the understanding of these techniques and optimizing their utilization in various industrial sectors, including aerospace, automotive, and biomedical engineering. The experimental analysis examines the impact of the Direct Metal Laser Sintering (DMLS) process parameter on sintering depth. The optimized parameters for AlSi10Mg alloy powder sintering were obtained using laser power at 162 W, scanning speed at 156 mm s−1, porosity at 20%, laser area size of 0.2 mm, and layer thickness of 1 mm.

Abrasive waterjet cutting of r‐GO infused magnesium fiber metal laminates: Experimental investigations and optimization through gorilla troops algorithm

AbstractLaminated metal‐composite structures, known as fiber metal laminates (FMLs), are modern lightweight materials extensively utilized in diverse industries such as aerospace and automotive manufacturing. These materials offer enhanced impact and fatigue resistance, making them invaluable for various applications. However, machining FMLs poses a challenge due to the occurrence of delamination and heterogenous in nature during conventional methods. Therefore, this study aims to investigate the quality characteristics such as kerf width, surface roughness and kerf taper of Magnesium based FMLs processed with an unconventional machining process namely abrasive water jet cutting (AWJC). These FMLs comprise alternately stacked kevlar/carbon fibers adhesively bonded with epoxy resin matrix filled with varying wt% of reduced graphene oxide (r‐GO), combined with AZ31B alloy sheet as the skin material. AWJC experiments were performed by varying the process parameters including waterjet pressure (275–325 MPa), stand‐off distance (2.5–3.5 mm), and cutting speed (600–800 mm/min) based on the box–behnken experimental design. The findings from the statistical analysis underscore the significant influences of stand‐off distance and waterjet pressure on kerf characteristics, while the inclusion of r‐GO is observed to notably affect the surface quality. In pursuit of enhancing cut quality, a multi‐response optimization was conducted employing the Gorilla Troops Optimization (GTO) algorithm. Comparative analysis with established metaheuristics like the gray wolf algorithm, dragonfly algorithm, and harmony search algorithm reveals GTO's superior performance across various metrics, including rapid convergence, diversity, and spacing values. Further, the cutting‐induced damages such as matrix plowing, fiber‐metal debonding and composite delamination were observed through microstructure analysis.Highlights Magnesium (AZ31B) fiber metal laminate comprising with various wt% of reduced graphene oxide was fabricated. Abrasive waterjet cutting of FMLs were performed based on box–behnken design experimental approach. Statistical analysis and influence of process parameters on the kerf width, surface roughness and kerf taper were investigated. Multi‐response optimization was carried out using metaheuristic‐based gorilla troops algorithm.

Comparing surface characteristics of Cu-Al-Fe alloys using thermal-based machining processes

The exceptional shape memory properties and load-handling capabilities of shape memory alloys makes them perfect for a spectrum of applications, such as actuators in robotics, control of aircraft wings and biomedical applications. Other than nickel-titanium shape memory alloy there are also various combinations of elements that show the same memory effect, namely Cu-Al-Fe, Cu-Al-Zn, and Cu-Al-Fe-Mn. However, a major problem often associated with shape memory alloys is the technical difficulty associated with machining them. Consequently, they do not tend to last longer when put to use. An optimal selection of input process parameters has a direct influence on the physical properties of these compounds. The traditional machining process, such as drilling, milling and grinding, pose a great threat to their properties. Hence, the research community has focused their study towards unconventional processes, such as (i) Wire Electric Discharge Machining, and (ii) Laser Beam Machining. In this research study, machining of the Cu-Al-Fe shape memory alloy was performed using three unconventional machining processes, namely (i) electric discharge machining (EDM), (ii) laser beam machining (LBM), (iii) powder-mixed electric discharge machining (PMEDM) and the effect of input process parameters were analysed. Various characterization tests provide useful information specific to changes in the microstructure and thermal behaviour of the alloy. The results show that the samples machined with PMEDM, EDM and LBM have surface roughness values of 2.377, 3.120 and 3.432 µm, respectively, which proves that PMEDM is best suited for machining the CuAlFe smart alloy.

Optimization of Wire EDM Process Parameters for Machining Hybrid Composites Using Grey Relational Analysis

The materials used in engineering have seen a significant transformation in the contemporary world. Numerous composites are employed to overcome these problems because conventional materials are unable to meet the needs of current applications. For quite some time, professional engineers and researchers have been captivated by the problem of choosing the best machining parameters for new composite materials. Wire electrical discharge machining is a popular unconventional machining process that is often used for making complex shapes. Numerous process parameters influence the WEDM process. Thus, to achieve affordable and high-quality machining, the right set of process parameters must be provided. Finding the wire cut EDM optimized settings for the fabricated LM5/ZrO2/Gr composite is the main aim of this research. The chosen input parameters are the wire feed, pulse on and pulse off times, the gap voltage, and the reinforcing percentage. In this study, LM5/ZrO2/Gr composites were made from stir casting with 6-weight percent ZrO2 as the reinforcement and varying graphite percentages of 2, 3, and 4 wt%. Then they were machined in WEDM using L27 OA to seek the best parameters for machining by adjusting the input parameters. The findings were analysed by means of grey relation analysis (GRA) to achieve the supreme material removal rate (MRR), lowest surface roughness (SR), and a smaller kerf width (Kw) simultaneously. GRA determines the impact of the machining variables on the standard characteristics and tests the impact of the machining parameters. Confirmation experiments were performed finally to acquire the best findings. The experimental findings and GRA show that the ideal process conditions for achieving the highest grey relational grade (GRG) are 6% ZrO2 with 2% graphite reinforcement, a wire feed of 6 m/min, a pulse off time (Toff) of 40 µs, a pulse on time (Ton) of 110 µs, and a gap voltage (GV) of 20 V. The gap voltage (22.87%) has the greatest impact on the GRG according to analysis of variance (ANOVA), subsequent to the interaction between the pulse on time and the gap voltage (16.73%), pulse on time (15.28%), and pulse off time (14.42%). The predicted value of the GRG is 0.679; however, the experimental GRG value is 0.672. The values are well-aligned between the expected and the experimental results. The error is only 3.29%, which is really little. Finally, mathematical models were created for each response.

Parameter Optimization Design of Plasma Arc Machining SS 304 Alloy by Means of Probabilistic Multi – objective Optimization

Plasma arc machining is an unconventional machining process, which is widely used to machine intricate part profiles of alloys with difficulty in general machine. In general, the surface roughness, kerf ratio, and material removal rate (MRR) are used as evaluation targets of the production process and quality of the machining samples; the plasma arc cutting parameters, such as arc voltage, standoff distance, cutting speed, and plasma offset, are employed as the input parameters for the cutting of SS 304 alloy machined at two different types of nozzles (130 A and 200 A). The parameter optimization design of plasma arc machining is a typical of optimal problem with multiple objectives. The employment of a rational multi – objective approach is quite important to the designers for the parameter optimization design of plasma arc machining. In this article, the probabilistic multi – objective optimization is utilized to conduct the parameter optimization design of plasma arc machining SS 304 alloy of thickness 6 mm, which is designed according to a mixed Taguchi design of L18 orthogonal array. The optimal parameters of plasma arc machining SS 304 alloy from the designed experiment for Nozzle 1 (130 A) are arc voltage at 136V, cutting speed of 2000mm/min, standoff distance of 2mm, and plasma offset of 2.25mm; the optimized parameters of plasma arc in machining SS 304 alloy from the designed experiment for Nozzle 2 (200 A) are arc voltage at 133V, cutting speed of 2000 mm/min, standoff distance of 2 mm, and plasma offset of 1.25mm. The results indicate the reasonability of the approach.

Effect of Wire Electrical Discharge Machining Parameters on various Tool Steels using Grey Relational Analysis

Materials having very high strength are causing hardship to machine using traditional machining methods. Therefore, consequently, unconventional machining process such as ECM, USM and EDM is developed for machining such materials. Wire EDM is an unconventional metal removal technology utilised to produce parts of any profile. Wire EDM machining parameters were optimised using Grey Relational Analysis for machining of tool steels such as H13, D2 and Oil Hardened Non-Shrinking Steels (OHNS). Optimum parameters are identified by conducting L27 OA experiment on H13, D2 and OHNS considering factors like GV, Ton, Toff and the wire feed by Taguchi based GRA method considering MRR, SR and cutting width (kerf) as the performance characteristics. Nine experiments were conducted with each tool. Objective is to obtain maximum MRR, minimum SR and minimum kerf simultaneously. The significance of the machining parameters was determined using ANOVA. From the response table and response graphs, the optimum process parameters were chosen. This method helped to improve the WEDM process.

Experimental Investigation on Bio-Machining of Nickel, Titanium and Nitinol (Shape Memory Alloys) Using Acidithiobacillus ferrooxidans Microorganisms

Micromachining plays a vital role in the manufacturing industry in producing microcomponents with high sensitivity and fine dimensional tolerances for implant materials in medical applications. Micro-machining can be carried out through various machining processes like physical, chemical and biological processes, although the use of biological machining is limited. In biological machining, microorganisms are used as a source of energy to machine the components, and machining with microorganism brings a lot of advantages in the machining process like the production of components with lower energy resources, low cost, no heat-affected zone and fine dimensional tolerances, which makes it suitable for machining implant materials. In other machining process like conventional and unconventional machining processes, the heat-affected zone, dimensional tolerances and environmental-related problems are the major issues, as these processes generate more heat while machining. This damages the material, which will not be able to be used for certain applications, and this issue can be overcome by bio-machining. In this present work, nickel, titanium and nitinol are manufactured using the powder metallurgy technique. They are manufactured as a 10 mm diameter and 5 mm thick pellet. The fabricated nickel, titanium and nitinol shape memory alloys are machined with Acidithiobacillus ferrooxidans microorganisms to obtain a better material removal rate and surface roughness and to check the bio-machining performance by considering various parameters such as shaking speed, temperature, pH and percentage of ferric content for the future scope of biomedical applications. Considering these parameters, microorganisms play a vital role in the temperature, shaking speed and time of the bio-machining process, and it was observed that a better material removal rate and surface roughness are achieved at a temperature of 30 °C, shaking speed of 140 rpm and machining time of 72 h.

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

Alumina‐Zirconium dioxide (Al2O3‐ZrO2) Ceramic Composite Material (CCM) is specifically known for its enhanced mechanical and corrosion resistance properties and is widely used as raw material for mechanical parts like, pump components, die inserts, bearings, etc. As a result, industrialists are searching for an efficient method for machining this Al2O3‐ZrO2 material. In this regard, a hybrid unconventional machining process called Electrochemical Discharge Machining (ECDM) is adapted to analyze the machinability of Al2O3‐ZrO2 CCM. Besides, to ensure the efficiency of the ECDM process, a magnetic field is also given to the tool electrode during this study to improve the Material Removal Rate (MRR) of the ECDM machine. The experiment is designed using Response Surface Methodology (RSM) by changing the magnitudes of input controls, namely Electrolytic Concentration (EC), Inter‐electrode Gap (IEG) and Applied Voltage (AV). Moreover, a novel hybrid machine learning optimization strategy called Deep Belief Network based Battle Royal Optimization (DBN‐BRO) algorithm is developed to predict and optimize the ECDM process. Finally, the optimum results are perceived from 55 V AV, 22.727% EC and 40.909 mm IEG input levels. The proposed method shows less than 0.6207 Root Mean Square Error (RMSE) and tools nearly 80 iterations for optimizing the results.

Optimization of process parameters in wire electrical discharge machining using teaching learning based optimization

The Un-Conventional or Non-Traditional machining process is aimed to produce products at right quality. WEDM (Wire electrode discharge machining) is unconventional advanced machining technique for better accuracy. In WEDM a thin wire is used to remove the material from the work piece through electrical spark. Parameters optimization plays a major role in machining process to achieve better quality. In this paper, a technique TLBO (teacher and learner based optimization) was used to parameters optimization in WEDM process of high speed steel (HSS) plates. Experimental values were taken from Sivanaga Malleswara Rao et al. (2017) article..

Eco-friendly MoS2/waste coconut oil nanofluid for machining of magnesium implants

Abstract The cost of the coolant and its disposal cost are significant issues in metal machining processes. In biocompatible magnesium alloy-based medical implants and instrument manufacturing, the cost hikes are owing to the use of unconventional machining processes and computerised numerical control machines. This research aims to improve machinability performance and optimize process parameters for biocompatible magnesium implant manufacturing for biomedical applications using eco-friendly nanofluid of MoS2 nanoparticles suspended in waste coconut oil. The nanofluid was prepared from the multiple times used waste coconut oil (waste) and was mixed with MoS2 nanoparticles. The orthogonal array L16, Taguchi analysis, and analysis of variance were employed in experimental design and statistical optimization. The machinability performance was determined by measuring and comparing the responses like cutting force, feed force, surface roughness, cutting zone temperature, and tool wear. They were compared with machining using a nanofluid and conventional commercial coolant. The results reveal that the proposed method of machining improved machinability performance appreciably; therefore, the observations of the proposed method were used and the process parameters were optimized. Mathematical models were developed for the prediction of process parameters. The proposed method exhibited the average reduction of the cutting force by 68.23167 N, feed force requirements by 34.180 N, the cutting zone temperature by 60.435°C, the surface roughness by 0.118908 µm, and the tool wear by 039938 mg·h−1.

Investigation of Abrasive Aqua Jet Hole Making (AAJHM) parameters using desirability analysis on Inconel-625 space alloy

Inconel-625 is one of the high-strength space alloys with wide applications in aerospace industries and corrosion resistance environments. The applications of Inconel-625 material require blind holes with adequate quality characteristics. In the conventional method, the hole-making on Inconel-625 is difficult due to its mechanical behaviour. The abrasive aqua jet machining process can cut hard and brittle materials among various unconventional machining processes. This work proposes to determine the ideal values of process parameters to generate quality holes on Inconel-625 space alloy by optimizing the abrasive aqua jet hole-making process parameters using a desirability analysis. Abrasive jet pressure (AJP), gap distance (Gdi), traverse speed (Tspeed), and abrasive mixture (Abrmix) of garnet and silicon carbide were identified as potential process variables. The quality hole surface is discussed through surface roughness (SR), erosion rate (Er), circularity error (CI), and cylindricity error (CY). The experimental investigation discloses that SR, CI, and CY decreased by 27.35 %, 56.23 %, and 42.56 %, and Er increased by 32.83 % when the AJP reached its higher value of 300 MPa. According to desirability analysis, the optimal level of machining parameters for numerous solutions is AJP = 300 MPa, Gdi = 1 mm, Tspeed = 96 mm/min, and Abrmix = 100%SiC (AJP-2, Gdi-2, Tspeed-1, Abrmix-2). The ANOVA investigation revealed that AJP was the most contributed parameter, trailed by Abrmix as 100%SiC. SEM and 3D images were used to analyze the surface topography of the hole surface of Inconel-625.

Investigation of WEDM parameters on Material Removal Rate and Plane Roughness of AISI4130 steel

Wire electrical discharge machine is a unconventional machining process. In WEDM Process more or less conductive materials only able to machined it. In WEDM material is removal from the work piece by continuous release of spark linking the work piece and the wire electrode. AISI 4130 low alloy steel is in recent times developed advanced materials having excellent material properties which will be used for aerospace and oil gas industry applications. In this paper the Experiments are conducted by using Tanguchi’s L18 orthogonal array and five input parameter voltage, current, pulse off time, pulse on time, wire type. Appling the ANOVA to conclude most significant machining parameter is voltage for the material removal rate and Plane Roughness

Laser beam drilling of fiber reinforced composites using Nd: YAG and CO2 Laser: A review

Laser beam drilling (LBD) is a non-traditional machining process used to machine the majority of engineering materials like alloys, super alloys, ceramics, and composites. Most advanced engineering materials are hard to machine using traditional machining methods because of their superior mechanical or surface properties. Laser beam machining is a versatile unconventional machining process that can be used on both conductive and non-conductive materials. Based on experimental and theoretical research using pulsed Nd: YAG and CO2 laser drilling of fibre materials such as PMMP, thermoplastic, and PAN, this paper report the various optimization techniques that are beneficial for achieving the responses. The research also begins to look into the possibility of using an Nd: YAG laser to drill geometrically accurate holes in fibre materials.

INFLUENCE OF PULSE DURATION ON SURFACE ROUGHNESS IN ASSISTING ELECTRODE ELECTRIC DISCHARGE MACHINING

Electrical discharge machining (EDM) is an unconventional machining process that can machine all electrically conductive materials, regardless of their physical and metallurgical properties. Due to the efficiency of machining modern engineering materials, existing EDM methods are constantly being researched and improved or developed. This paper deals with an innovative method that enables EDM machining of non-conductive ceramic material, named Assisting Electrode Electrical Discharge Machining (AEEDM). It combines electrical discharge machining with a hybrid assisting electrode. The aim of the study is to find the influence of pulse duration on surface roughness. For the set machining conditions, it was found that the surface roughness was increased by increasing the pulse duration. It should be emphasized that the supporting electrode method is used only in the electroerosion of electrically non-conductive materials.

Understanding the behavior of Bancassurance service in India

This study is in developing India to develop policy recommendations for bancassurance markets Banking and Insurance in Europe Coordination of sub-sectors Discusses functional benefits. In the 1990s in European countries banking and When financial consolidation of insurance services began, most banks and insurance companies already do Some are listed for a period of time. Efficient frontier portfolio in European bancassurance markets and We study pairwise combinations. The current investigation in selecting alternatives in the supply chain Based on ratio analysis (MOORA). including multi-objective optimization Fuzzy MCDM technique is used. For selecting supply chain strategies MOORA Method is applied to three relevant numerical examples. In the operational research field, many MCDM methods have been developed in the previous period, highly specific and No extension yet. Therefore, in this paper, Perfect for solving many complex real-world problems an extended to propose the MOORA method, Space gray numbers and We integrate the MOORA method. The present study investigates a new technique called multi-objective optimization based on Ratio Analysis (MOORA) Faced with real-time manufacturing industries Solves a variety of multi-purpose problems. It's with many benchmarking issues Solves some unconventional machining processes. The alternative is Life insurance (MEAN SR), Life insurance (STD SR), Life Insurance (CV), Non-life insurance (MEAN SR), Non-life insurance (STD SR), Non-life insurance (CV), Insurance broker (MEAN SR), Insurance broker (STD SR), Insurance broker (CV). Evaluation parameter is insurance percentage, 0, 10, 25, 50, 75, 90, and 100. In this paper Bancassurance with insurance companies for Non-life insurance (CV) is got the first rank whereas is the Insurance broker (STD SR) is having the Lowest rank.

Influence of Coated Electrode in Nanopowder Mixed EDM of Al–Zn–Mg–Si3N4 Composite

Machinability investigation of new material is one of the mandatory investigations to complete the purpose of creation of it. Electrical discharge machining (EDM) is one of the promising unconventional machining processes for highly accurate machining performance in difficult-to-cut material even machining complicated profiles. The powder-mixed EDM and nanopowder-mixed EDM are the improved versions of the EDM. The Al–Zn–Mg composite is reinforced with Si3N4 (9 wt. %) for meeting automotive and marine applications. The aluminium nanoparticles enhanced deionised water was used in NPMEDM. The nickel-coated brass and uncoated brass tube electrode were considered for the investigation. Pulse on time (µs), voltage (V), input current (A), and capacitance (nF) were independent variables and varied at 3 levels. The microhole machining performance with a coated and uncoated electrode was investigated. The L18 orthogonal array involved in the experimental design, material removal rate, and electrode wear rate were analysed. The SEM analysis was employed in the surface morphological study of electrodes before and after machining. The input parameters were optimised for the coated electrode for the responses of MRR and EWR.

Investigation and Process Parameter Optimization on Wire Electric Discharge Machining of Aluminium 6082 Alloy

Wire electrical discharge machining (WEDM) is an unconventional machining process that is being extensively used in the aerospace,medical devices, die, tooling, and automotive industries for machining high-hardness materials with conductivity. In the present work, WEDM of aluminium 6082 alloys was carried out since it influences diversified applications in manufacturing industries. The WEDM process includes an extensive number of variables that influence its execution. However, based on the literature survey, three process parameters such as pulse-on time (PTON), pulse-off time (PTOFF), and wire feed (WF) were taken into consideration. The factorial design was used for the selection of parameter levels and arrived at the 27 trails for the machining. The output responses of the WEDM, namely, surface roughness (SR), kerf width (KF), and metal removal rate (MRR) were measured, and its parameter optimization was also carried out to minimize the significant effect on productivity and the quality of components. The measured output response was compared with the predicted response surface methodology (RSM) results; it was found that the SR and KF values decreased with the increase of PTON. The MRR was increased with the increase of PTON.