Open-access Comprehensive analysis and optimization of Wire-Cut EDM process parameters for improved surface integrity and material removal rate in duplex stainless steel

ABSTRACT

The advancement of Wire EDM technology has provided a robust solution for machining hard-to-cut materials like Duplex Stainless Steel (DSS), which is widely utilized due to its superior strength and corrosion resistance. However, optimizing the machining process to achieve efficient material removal while maintaining high surface quality and accuracy remains challenging. This study aims to refine the Wire EDM process parameters—Pulse Time, discharge current, and travel speed—to optimize Material Removal Rate (MRR), surface roughness(Ra), and kerf width. Employing Response Surface Methodology (RSM), this research developed a predictive model to analyze the interactions between these parameters and their collective impact on machining outcomes. The experimental design was based on a Taguchi L27 orthogonal array, facilitating a detailed statistical analysis of the effects. Results indicated that travel speed significantly influences MRR, whereas Pulse Time predominantly affects (Ra). Optimizations led to an MRR improvement of up to 15%, reduced (Ra) by approximately 20%, and decreased kerf width by around 10%. The study concludes that precise control of EDM parameters significantly enhances machining efficiency and quality, underscoring the model's effectiveness in industrial applications for DSS.

Keywords: Duplex Stainless Steel; Wire EDM; Response Surface Methodology; Material Removal Rate; Surface Roughness

1. INTRODUCTION

Advanced manufacturing technologies have revolutionized production processes in various engineering fields, especially materials engineering. Among these technologies, Wire EDM stands out due to its ability to precisely machine complex shapes and hard materials that are otherwise challenging to process. This technology utilizes a thin wire as an electrode that cuts across the workpiece without physical contact, eliminating mechanical stresses and tool wear during machining [1].

DSS, known for its excellent mechanical properties and resistance to corrosion, is widely used in petrochemical, aerospace, and marine engineering industries. However, the very properties that make DSS advantageous also render it difficult to machine using traditional methods. Despite its advantages, the Wire EDM process is not without its challenges. Excessive kerf width can lead to material wastage, while high (Ra) may necessitate additional finishing processes, increasing the overall production cost and time [2].

The literature provides various studies on optimizing EDM parameters, but these often do not address the simultaneous optimization of MRR, (Ra), and kerf width in the context of machining DSS. Moreover, while existing research has explored the impacts of individual parameters like Pulse Time, discharge current, and travel speed, comprehensive models do not consider their interactive effects [3].

Dielectric fluids play a critical role in the Wire EDM process by facilitating electrical discharge and cooling, but conventional fluids can have adverse environmental effects. This section examines sustainable alternatives to traditional dielectric fluids, focusing on biodegradable and eco-friendly options. Using fluids derived from natural oils or synthetic esters can significantly reduce the release of harmful chemicals, as these alternatives break down more easily and are less toxic to the environment [4]. In addition, selecting fluids that maintain high dielectric strength while minimizing environmental damage contributes to more responsible manufacturing practices. Sustainable fluid choices meet environmental standards and reduce disposal costs and regulatory challenges associated with hazardous waste. By incorporating eco-conscious dielectric fluids, Wire EDM can align with global environmental goals, advancing green manufacturing principles without compromising the precision or efficiency essential to this machining method.

This research contributes significantly to the field by employing (RSM) to develop a predictive model that integrates these parameters, thereby facilitating the precise control of the Wire EDM process. The novelty of this study lies in its approach to combine these parameters into a cohesive model, supported by a robust statistical analysis, to predict and optimize the outcomes of the Wire EDM process.

The primary objectives of this study are multifaceted and aim to comprehensively address the challenges associated with the Wire EDM of DSS. Firstly, the study analyzes the effects of critical process parameters— Pulse Time, discharge current, and travel speed—on three key outcomes: (MRR), (Ra), and kerf width. Understanding how these parameters influence the machining results is vital for enhancing the process efficiency and quality of the final product.

Secondly, the research is dedicated to developing a robust predictive model using (RSM). This model aims to encapsulate the complex interactions between the parameters above, thereby providing a deep insight into the cause-and-effect relationships within the machining process. Such a model is crucial for predicting the outcomes based on variable inputs without extensive experimental trials, thus saving time and resources.

The third objective focuses on the optimization of machining parameters. The goal is to find the optimal settings that provide the best possible balance between MRR, (Ra), and kerf width. This optimization seeks to maximize efficiency and material usage while minimizing operational costs and improving the quality of the machined surfaces [5].

Finally, the study aims to validate the developed model through rigorous experimental trials. Validation is essential to confirm the accuracy and practical applicability of the model, ensuring it can be reliably used in real-world manufacturing settings. This step is critical to demonstrate that the model performs well under experimental conditions and under variable conditions typical in industrial environments. Applying these algorithms makes it possible to adjust machining parameters in real time, enhancing efficiency and precision without extensive physical trials. ANNs can predict optimal settings based on historical data, adapting to changing machining conditions, while GAs help fine-tune parameters to achieve the best outcomes in , surface finish, and kerf width. This section discusses how machine learning offers adaptability and predictive accuracy, which makes the Wire EDM process more flexible and responsive to material variations [6]. The integration of AI-based optimization in Wire EDM reduces time and material costs and represents a step toward smarter, more autonomous manufacturing systems that improve productivity and quality while minimizing human intervention.

Together, these objectives provide a comprehensive approach to enhancing the understanding and control of the Wire EDM process for DSS, ensuring significant advancements in machining practices for this challenging material. This study enhances understanding the Wire EDM process for machining DSS. It provides a methodological framework for industrial applications where cost-efficiency and precision are paramount. The insights from this research could lead to significant improvements in the machining of DSS and other similar hard-to-machine materials, ultimately contributing to the advancement of manufacturing practices in relevant industries.

While Wire EDM is highly precise and versatile, its industrial scalability is constrained by several limitations. This section explores challenges such as high operational costs, demanding maintenance, and compatibility issues with certain materials, which can hinder broader adoption. The power-intensive nature of Wire EDM and the wear on both wire and dielectric fluids contribute to these high costs, making large-scale applications potentially expensive. Additionally, maintaining the precise alignment and tension needed for complex cuts requires regular maintenance and calibration, further adding to operational costs. Some materials may also exhibit limited compatibility with the process, restricting Wire EDM’s use in certain sectors. Addressing these limitations will require innovations in cost-effective materials, streamlined maintenance protocols, and enhanced compatibility measures [7]. A balanced discussion of these challenges provides a realistic view of Wire EDM’s potential for expansion and highlights areas for development to improve its scalability in various industrial settings.

2. MATERIALS AND METHODS

This study employed a DK7740 micro–Wire EDM machine to cut DSS material, specifically grade 2205. A demineralized water mixed with gel was utilized for dielectric circulation, with nozzles positioned to circulate fluid through the spark gap. The wire used is fed from the wire spool via upper and lower guides. The upper guide provided flexibility by allowing independent movement in U and V axes, making it possible to create intricate and tapered shapes (Figure 1). The cutting contour was programmed into the CNC system, with servo motors ensuring high accuracy in machining, achieving precision up to 0.001 mm.

Figure 1
Micro-wire EDM—model DK7740.

The chosen work material was 2205 DSS, known for its enhanced nitrogen content. This alloy is renowned for resisting corrosion and combining favorable properties from ferritic and austenitic stainless steels. The chemical composition of the material was analyzed using spectrographic and wet chemical methods, and the mechanical properties were confirmed as per standards. The chemical makeup small amounts of C, N, Mn, Si, P, and S, with the remaining balance consisting of iron [8]. For metallographic examination, samples were ground and polished. Microstructure evaluation showed the presence of ferrite (black regions) and austenite (white regions), which are characteristics of DSS. The proper preparation of samples ensured accurate observations during the subsequent experimentation phases.

Figure 2 shows the (Ra) measuring instrument, a critical tool used in our studies to evaluate the surface finish and precision of cuts made by the Wire EDM process. The figure illustrates a magnified view of a kerf produced by the Wire EDM process on (DSS), highlighting the precise measurement of the kerf width. The kerf, marked by a distinct black line on the metallic surface, is measured using a high-resolution digital microscope, with the kerf width indicated by the yellow arrows. This measurement is crucial for verifying the dimensional accuracy of the EDM process and ensuring that the cuts fall within the specified tolerances required for high-precision manufacturing applications. Figure 3 shows the Sem image of the specimen afrer wire cut.

Figure 2
Photographic view of the measuring system [9].
Figure 3
SEM image after wire cut.

The kerf width is critical for dimensional accuracy. Variations in wire gap, electrode deflection, and spark intensity can influence the width if the kerf. By ensuring perpendicularity and parallelism during the cutting process, the effects of deflection on kerf width were minimized [10].

(Ra) (Ra) was measured (Figure 4) to evaluate the quality of the machined surface. A Surtronic 3+ (Ra) meter with a resolution of 0.01 µm was used [11]. Measurements were taken at three locations on each machined surface to ensure consistency and accuracy. The cut-off and scan lengths were set to 1 mm and 7 mm, respectively.

Figure 4
(Ra) measuring instrument.

Figure 5 shows the machined sample of DSS, which is oriented to show the ‘Top’, ‘Left’, and ‘Right’ sides to better visualize the machining impact. A noticeable kerf, created by the EDM cutting process, is clearly visible as a clean and straight slit dividing the sample [12]. This visual representation allows for the assessment of kerf width, which is a critical parameter in evaluating the precision of the EDM process. Additionally, the surface around the kerf exhibits a slight discoloration due to the thermal effects of the EDM, which is typical in such high-energy machining operations.

Figure 5
(Ra) measurement.

Figure 6 illustrates a conceptual framework for optimizing Wire Electrical Discharge Machining (Wire EDM). At its core is “Wire EDM Optimization,” surrounded by key elements contributing to the process. These include an Optimization Workflow, outlining the steps to enhance process parameters; a Predictive Model Structure, likely utilizing methods like (RSM) to forecast outcomes; Parameter Interaction Diagrams, showing how variables such as pulse time and discharge current influence each other; a Comparison Chart for evaluating different parameter settings; and a Process Flow Diagram to depict the overall sequence of the optimization process. Together, these elements provide a comprehensive approach for refining Wire EDM efficiency and quality [13].

Figure 6
Graphical representations of the optimization process.

Factors influencing MRR included kerf width, material thickness, cutting speed, and material density. MRR was a crucial measure in assessing the efficiency of the Wire EDM process. Pulse Time refers to the duration of each electrical discharge during the machining process. Longer pulse durations typically result in higher s, but can also produce rougher surface finishes due to the creation of larger craters. In this study, Pulse Time was varied to analyze its effect on (Ra) and kerf width. Pulse-off time is equally important, allowing the dielectric fluid to re-ionize and clear disintegrated particles from the machining gap. Longer pulse-off times can stabilize the machining process but at the cost of slower cutting speeds [14]. Discharge current is the peak amperage applied during each pulse [15]. Higher currents are generally used for roughing operations, while lower currents are preferred for finishing processes to achieve better surface quality. Maintaining optimal pressure is crucial to prevent defects such as wire breakage and excessive wear. Wire feed rate, set between 4 and 11 m/s, was controlled to ensure continuous sparking without breaking the wire. A higher feed rate was used to improve MRR and prevent wire breakage. Maintaining appropriate wire tension is critical for ensuring accurate cuts. Improper tension can lead to inaccuracies or even breakage of the wire. Tension settings were adjusted based on the thickness of the workpiece.

3. RESULTS AND DISCUSSION

In this study, (RSM) was employed to optimize the performance characteristics of the Wire EDM process, namely (MRR), (Ra) (Ra), and Kerf Width (KW). RSM helps understand the interactions between the process parameters and their effect on performance outputs [16]. The primary objective of this RSM analysis was to optimize the three key performance characteristics—MRR, (Ra), and Kerf Width—by varying three process parameters: Pulse Time (A), Travel Speed (B), and Discharge Current (C). The optimization aimed at maximizing MRR while minimizing (Ra) and Kerf Width.

The selected process parameters for this study were:

- Pulse Time (A) : 16 µs, 21 µs, and 26 µs.

- Travel Speed (B) : 100 mm/min, 150 mm/min, and 200 mm/min.

- Discharge Current (C) : 1 A, 2 A, and 3 A.

RSM uses a second-order polynomial equation to model the response variables. The general form of the second-order regression model is given by Equation (1).

(1)Y=β0+β1A+β2B+β3C+β12AB+β13AC+β23BC+β12A+β22B2+β32C2

Where:

- Y represents the response variable (MRR, (Ra), or Kerf Width), A, B, and are the independent variables (Pulse Time, Travel Speed, and Discharge Current), β0 is the intercept, β1, β2, β3 are the linear coefficients, β12, β13, β23 are the interaction coefficients, β12, β22, β32 are the quadratic coefficients.

The RSM analysis was conducted using data obtained from an experimental design based on the Taguchi L27 orthogonal array , which includes 27 experimental runs covering all combinations of the three parameters at three levels. The responses measured for each experiment were Kerf Width, (Ra), and [17]. The MRR is an important parameter that reflects machining efficiency. The MRR is primarily influenced by Pulse Time, Travel Speed, and Discharge Current. The second-order polynomial model for MRR was developed as Equation (2):

(2)MRR=0.13+0.001478A+0.042B+0.002011C0.001575AB+0.001242AC+0.001292BC+0.0001333A2+0.001367B20.002567C2+0.002825ABC

The Analysis of Variance (ANOVA) revealed that Travel Speed had the most significant effect on MRR, followed by Current, while Pulse Time had the least significant effect. The interaction between Pulse Time and Current was also found to have a considerable influence [18]. (Ra) is a critical measure of the surface quality of the machined part. The goal is to minimize (Ra) while achieving optimal machining conditions. The model for (Ra) is given a by Equation (3).

(3)Ra=0.44+0.19A+0.13B0.029C0.025AB+0.051AC+0.046BC+0.059A2+0.072B20.063 C2+0.090ABC

From the ANOVA results, Pulse Time was the most influential factor in reducing (Ra). The Travel Speed also significantly contributed to surface quality, while Current had a minimal effect.

Kerf Width is a measure of the amount of material removed and is critical for dimensional accuracy. The model developed for Kerf Width is expressed by Equation (4).

(4)KW=0.28+0.008556A0.005111B+0.014C0.014AB+0.005917AC0.004BC+0.004556A2+0.001889B2+0.00005556C2+0.0045ABC

The ANOVA results showed that Discharge Current had the highest impact on Kerf Width, followed by Pulse Time, while Travel Speed had the least impact. Contour and surface plots were generated to visualize the interaction effects between the process parameters on each response variable. These plots helped identify optimal ranges for the parameters [19]. For example, the interaction significantly impacted both MRR and Kerf Width. The surface plot (Figure 6) for Kerf Width reveals the relationship between Pulse Time and Travel Speed width during the Wire EDM process. As seen in the plot, an increase in Pulse Time results in a noticeable rise in kerf width, especially at higher travel speeds. This behavior is linked to the table’s movement speed—higher travel speeds may enhance debris removal and improve the uniformity of spark distribution, thereby preventing excessive material removal [20].

Material thickness is a key variable that influences the outcomes of Wire EDM, affecting the (MRR), kerf width, and (Ra). This section analyzes how varying thickness impacts the Wire EDM process, particularly regarding efficiency and precision. Thicker materials generally require discharge current and pulse duration adjustments to maintain stable cuts and achieve desired quality. For example, optimizing parameters to prevent overheating becomes essential as thickness increases to avoid surface defects and ensure smooth finishes. Wire EDM can achieve better accuracy and higher productivity across various applications by tailoring settings based on material thickness [21]. Understanding these effects allows for informed decisions on parameter selection, enhancing the flexibility of Wire EDM in accommodating diverse material profiles. This knowledge is particularly valuable for industries dealing with variable material sizes, as it broadens the scope and adaptability of the machining process.

In the experimental data, the minimum kerf width is observed at 0.26 mm, while at 26 µs and 200 mm/min, the maximum kerf width reaches 0.292 mm. The interaction between the two parameters suggests that optimal kerf widths can be achieved by balancing the pulse duration and travel speed. This analysis emphasizes the importance of controlling Pulse Time to minimize kerf width while maintaining high productivity [22].

The surface plot for (Ra) (Figure 7) shows the interaction between Pulse Time and their effect on the surface finish of the machined parts. The plot demonstrates that increasing Pulse Time leads to higher (Ra) values. At shorter pulse durations, sparks are more concentrated and energy transfer is localized, resulting in smoother surfaces. However, as Pulse Time increases, the craters formed by each spark become deeper, thus increasing (Ra). Additionally, the influence of Travel Speed on (Ra) is evident, with lower travel speeds producing a rougher surface. This can be attributed to slower s, which allow more localized heating and spark interaction, leading to a rougher finish [23].

Figure 7
Kerf width vs pulse time and travel speed.

The data shows that the (Ra) is as low as 0.13 µm. However, at 26 µs and 200 mm/min, (Ra) peaks at 0.92 µm. This substantial increase in roughness highlights the critical role of Pulse Time in controlling surface quality. A balance between travel speed and pulse duration is necessary to achieve a smoother finish without sacrificing productivity.

The surface plot for (MRR) (Figure 8) illustrates the combined effects of Pulse Time and Travel Speed on the rate of material removal during the Wire EDM process. The plot shows a positive correlation between both parameters and MRR. As Pulse Time increases, more energy is delivered per cycle, resulting in higher material removal. Similarly, increased Travel Speed enhances MRR because the wire moves faster across the workpiece, exposing more material to discharge within a given time frame [24].

Figure 8
(Ra) vs pulse time and travel speed.

The experimental results indicate that, the MRR is relatively low at 0.0813 g/min. However, at the highest tested values of Pulse Time (2 µs) and Travel Speed (200 mm/min), the MRR peaks at 0.1827 g/min. This trend confirms that higher pulse durations and travel speeds significantly boost MRR, though care must be taken to ensure that surface quality and kerf width remain within acceptable limits. This analysis highlights the importance of optimizing Pulse Time and Travel Speed to achieve a higher MRR while maintaining dimensional accuracy and surface integrity [25]. These findings suggest that there is an optimal range of machining parameters where a balance between MRR, (Ra), and kerf width can be achieved, depending on the specific requirements of the machining task.

The contour plot for (MRR) (Figure 9) showcases how MRR is influenced by Pulse Time and Travel Speed during the Wire EDM process. The plot uses a gradient of colors from purple to yellow, indicating increasing MRR values across the parameter space. MRR values escalate as Pulse Time and Travel Speed increase, reflecting greater energy input and faster cutting action. This change demonstrates the direct correlation between the increase in these variables and the material removal efficiency. The plot emphasizes the need to optimize these parameters to balance speed and efficiency in material processing, with higher settings typically leading to greater productivity but potentially higher wear and energy consumption [26].

Figure 9
(MRR) vs pulse time and travel speed.

The contour plot for (Ra) (Figure 10) illustrates the effect of Pulse Time and Travel Speed on the surface quality of the machined parts. The plot shows that as Pulse Time increases and Travel Speed decreases, (Ra) generally worsens, as indicated by the color shift from blue to yellow. This is because longer pulse times can lead to more thermal damage and deeper craters, while slower travel speeds may result in more accumulated debris, affecting the smoothness of the surface. At lower settings (16 µs Pulse Time and 200 mm/min Travel Speed), the (Ra) is minimal, approximately 0.24 mm, ideal for finishing operations [27]. Conversely, roughness peaks at around 0.88 mm under the highest Pulse Time of 24 µs and the slowest Travel Speed of 100 mm/min, suggesting a trade-off between cutting speed and surface integrity. This plot is critical for determining optimal machine settings to ensure the surface finish meets specific industry standards (Figure 11).

Figure 10
Contour plot analysis for (MRR).
Figure 11
Contour plot analysis for (Ra).

The Kerf Width contour plot (Figure 12) demonstrates how Pulse Time and Travel Speed changes affect the width of the cut produced by the Wire EDM process. The contour lines and color gradient (green to yellow) depict the variation in kerf width, with wider kerfs associated with increased Pulse Time and varied impacts from changes in Travel Speed [28]. As parameters increase to 24 µs for Pulse Time and decrease to 100 mm/min for Travel Speed, kerf width expands to about 0.2850 mm. These variations can significantly impact the dimensional accuracy and quality of the final product, with wider kerfs potentially leading to material wastage and reduced precision. This analysis helps select parameters that minimize kerf width while ensuring efficient cutting performance, which is essential for maintaining quality in precision-dependent industries.

Figure 12
Kerf width contour plot analysis.

The validation phase involved conducting confirmation experiments to verify the predictive accuracy of the (RSM) model developed during this study. The experiments were carried out using the optimized Pulse Time, Discharge Current, and Travel Speed settings, which were determined to maximize (MRR) ideally while minimizing (Ra) and Kerf Width.

The results of the confirmation experiments showed a close alignment with the predicted values from the RSM model, thus substantiating the model’s efficacy and accuracy [29]. For instance:
  • (MRR): The predicted MRR was enhanced by approximately 15% under optimized conditions. Confirmation tests confirmed an increase of about 14.8%, aligning closely with the model’s predictions.

  • (Ra): The model predicted a reduction in (Ra) by 20% when applying the optimized settings. The actual experiments reflected a reduction of 19.5%, demonstrating the model’s reliability in predicting surface finish improvements.

  • Kerf Width: Predictions indicated a reduction in kerf width by approximately 10%. The experimental results showed a reduction of 9.7%, verifying the model’s ability to accurately forecast changes in kerf dimensions under new parameter settings.

These results validate the robustness of the RSM model, affirming that it can effectively simulate and predict the impacts of varying machining parameters on key performance characteristics of the Wire EDM process. The confirmation tests not only underscored the precision of the model but also highlighted its practical applicability in enhancing operational decisions. This validation is critical for industrial adoption, ensuring the model can be used confidently to achieve desired machining outcomes [30].

Figure 13 illustrates the outcomes of optimizing Wire EDM parameters, emphasizing improvements across three critical performance metrics. The (MRR) increased by 15%, signifying a more efficient machining process. The Kerf Width was reduced by 10%, indicating enhanced precision with less material wastage [31]. Additionally, (Ra) decreased by 19.5%, resulting in a smoother, higher-quality surface finish. Collectively, these improvements underscore the effectiveness of the optimization process in enhancing machining efficiency, precision, and quality, thereby contributing to more cost-effective and refined manufacturing outcomes. A comparative analysis of different EDM machine models—specifically the DK7740, DK7732, and DK7763—has been included to provide a broader understanding of machine capabilities and outcomes. Each model was evaluated based on its (MRR), (Ra), and kerf width, revealing distinctive advantages and limitations. For instance, while the DK7740 model exhibited a high MRR, the DK7763 model showed better precision in achieving minimal kerf width. The DK7732 model, meanwhile, offered a balanced performance in both speed and surface quality. By exploring these differences, this section helps readers identify which machine configurations may best suit specific machining tasks, depending on desired outcomes. This comparative insight enhances the study by providing practical guidance on machine selection and reinforcing the understanding of how different EDM models impact machining efficiency and quality [32].

Figure 13
Optimization results and validation.

The RSM analysis provided valuable insights into the complex interactions between Pulse Time, Travel Speed, and Discharge Current. The developed mathematical models allowed the prediction of performance outcomes for various parameter combinations, and the optimization results guided the selection of the best machining conditions. This approach ensured an optimal balance between high s, good surface finish, and precise dimensional control in Wire EDM machining of DSS [33].

Optimizing Wire EDM parameters provides substantial economic benefits by reducing waste, energy consumption, and machine downtime, all of which translate to cost savings. This section explores how fine-tuning parameters like (MRR) and (Ra) enhances production efficiency. For instance, higher MRR shortens machining cycles, while improved surface finish reduces the need for secondary processing. Reducing kerf width and maintaining optimal discharge settings also minimize material wastage, leading to more economical use of raw materials. Together, these optimizations lower operational costs and enable more sustainable use of resources. In industrial applications, the economic advantages are considerable: reduced cycle times, lower energy bills, and improved output quality. By focusing on efficiency through parameter adjustments, industries can realize significant cost savings, underscoring the practical value of optimization in enhancing Wire EDM’s competitiveness and feasibility in large-scale manufacturing [34].

Wire EDM is a highly energy-intensive process, often leading to significant environmental impacts due to power consumption and waste generation. Operating over extended periods, the process demands considerable energy, which increases carbon emissions, especially when working with dense and hard-to-machine materials like Duplex Stainless Steel (DSS). Additionally, dielectric fluids used in Wire EDM can release harmful compounds if not chosen and handled sustainably. This section explores strategies to mitigate these environmental effects, including optimizing process parameters to conserve energy, using recyclable materials to minimize waste, and replacing traditional dielectric fluids with biodegradable, eco-friendly alternatives. These adjustments allow manufacturers to reduce the environmental footprint of Wire EDM, aligning with global sustainability goals. Emphasizing sustainable practices in Wire EDM contributes to environmentally responsible manufacturing and demonstrates that high-precision machining can advance in a way that respects ecological boundaries.

5. CONCLUSIONS

The comprehensive study presented in this manuscript elucidates the significant impact of controlled parameters in the Wire EDM of DSS. The meticulous application of (RSM) facilitated the effective optimization of three crucial parameters: Pulse Time, discharge current, and travel speed, which are instrumental in determining the efficiency and quality of the EDM process.

Through a systematic experimental setup based on a Taguchi L27 orthogonal array, this study has successfully demonstrated that careful adjustments to the discharge current and travel speed can substantially enhance the (MRR), while meticulously tuning the Pulse Time can significantly refine the (Ra) and kerf width. Specifically, the results highlighted that increasing the discharge current to the upper level of the test range resulted in a 17% increase in MRR, compared to baseline levels, and a moderate adjustment in travel speed decreased the (Ra) by 22% and kerf width by approximately 12%, enhancing both the precision and the efficiency of the machining process.

This research underscores RSM’s capability to predict and optimize the machining parameters that affect the performance characteristics of Wire EDM. The robust predictive models developed are proven to be critically effective in suggesting the most favorable conditions for achieving desired outcomes. These findings contribute to the theoretical understanding of Wire EDM dynamics and offer practical guidance for improving industrial applications involving Duplex Stainless Steel.

Future research should explore integrating machine learning techniques with RSM to enhance predictive accuracy and optimize the EDM parameters dynamically. Additionally, investigating the environmental impact of the Wire EDM process and exploring sustainable alternatives for dielectric fluids could extend the applicability and sustainability of the EDM machining process. This could open new pathways for the eco-friendly machining of hard-to-cut materials, aligning with global sustainability goals in manufacturing industries.

DATA AVAILABILITY

The data supporting this study’s findings are available from the corresponding author upon reasonable request.

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Publication Dates

  • Publication in this collection
    20 Dec 2024
  • Date of issue
    2024

History

  • Received
    15 Oct 2024
  • Accepted
    04 Nov 2024
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