Machining performance, economic and environmental analyses and multi-criteria optimization of electric discharge machining for SS310 alloy | Scientific Reports

Scientific Reports volume 14, Article number: 28930 (2024) Cite this article

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With the expansion of the manufacturing sector, it has become crucial to incorporate sustainable production methods in order to remain competitive in the market. This study focuses on addressing the needs of the manufacturing industry by conducting a sustainability analysis of electric discharge machining for SS310 alloy. The analysis explores the impact of various electrode materials, for instance, copper and brass, as well as different machining variables, including discharge current (I = 4–12 A), spark gap (SG = 6–12 mu), pulse duration (Pon = 15–45 μs), and duty cycle (DC = 75–85%) using Taguchi method. The objective is to optimize the machining performance measures, which includes material removal rate (MRR), surface roughness (Ra), electrode wear (EW), and energy consumption (EC). In addition, the economic analysis of the machining process takes into account factors such as energy cost, dielectric consumption cost, EW cost, labor cost, and machine depreciation cost for both types of electrodes. Furthermore, the study investigates the carbon emissions resulting from EC, dielectric consumption, and EW to assess the environmental impact of the machining process. Multi-criteria decision-making approach is employed to assess the sustainability of the machining process by taking into account several performance, cost and environmental factors simultaneously. From empirical analysis, it has been observed that the copper electrode outperformed the brass electrode in terms of MRR (2.67 mm3/min), Ra (3.36 µm), EW (0.272 g), and EC (145.08 kJ) due to its superior electrical and thermal characteristics. In the cost analysis, copper offered lower costs for EC (2.02 PKR) attributed to its higher electrical conductivity while higher costs in terms of EW (5.5 PKR) and dielectric consumption (5.2 PKR) than brass. However, the analysis of labor and machine depreciation costs revealed that the application of copper electrode results in lower costs (80.1 and 99.3 PKR, respectively) than the brass electrode primarily due to its shorter machining time. The analysis of the environmental impact showed that the utilization of a copper electrode leads to reduced carbon emissions of 9.8 g CO2 due to its lower EC during the machining process. However, the copper electrode results in higher emissions from EW (5.07 g CO2) and dielectric consumption (54.58 g CO2) compared to the brass electrode. Based on the multi-criteria decision-making using the composite desirability function approach, it is evident that the copper electrode exhibits superior performance in terms of MRR, Ra, and total machining cost. Conversely, the brass electrode demonstrates better performance in terms of overall carbon emissions.

The contemporary paradigm of economic growth is extensively reliant on the consumption of fossil fuels, which serves as the primary catalyst for the emission of carbon dioxide (CO2)1. The carbon dioxide emissions contribute significantly to climate change and global warming, posing severe threats to humans, ecosystems, and biodiversity survival2. In recent times, there has been a noticeable increase in global awareness and the significance of energy conservation, pollution mitigation, healthcare issues, and environmental considerations3. Governments are actively promoting the need to address these concerns and reduce their impact. According to the reports, 604 exajoules of energy were consumed globally in 2022, with an increase of 1.1% in comparison to 20214. The manufacturing sector accounted for the consumption of 166 exajoules of global energy in 20225. The significance of energy efficiency in the manufacturing industry has grown in response to governmental restrictions. Sustainable Manufacturing has emerged as a strategic methodology for producing goods that effectively balance cost considerations with environmental considerations6. This approach prioritizes the reduction of waste generation, the optimization of renewable energy utilization, and the overall efficiency enhancement of the manufacturing process7. Sustainable manufacturing is mainly based on four major pillars: (i) Productivity, (ii) Quality, (iii) Economic aspects, and (iv) Environmental efficiency. To achieve sustainability in the manufacturing process, it is essential to meet the aforementioned criteria. In this regard, manufacturing processes such as electric discharge machining (EDM), which mainly rely on spark discharge energy for material removal, need to be evaluated for their energy efficiency8.

EDM is widely used in machining materials that are difficult to cut because it does not require the tool and the workpiece to come into direct physical contact9. Electrical sparks between the workpiece material and tool are produced during EDM, which causes the interfacial zone’s temperature to rise significantly to as high as 12,000 °C; the substance of the workpiece is removed by melting and evaporation10. Typically, both the workpiece and the face of the electrode are submerged in a dielectric fluid, where the electric sparks are produced11. In the EDM process, numerous machining factors related to spark discharge, dielectric fluid and electrode material are generally considered to optimize the machining performance12. Among them, discharge current (I), open voltage, pulse on time (Pon), pulse off time (Poff), and spark gap (SG) are the parameters which directly influence the spark discharge13. The type of dielectric fluid and flushing pressure are the prime variables related to dielectric fluid. Electrode materials, including copper, brass, stainless steel, graphite, aluminum, and copper-tungsten, are also considered key variables in improving machining performance14. Several response measures, such as MRR, Ra, white layer thickness, tool wear rate, and dimensional accuracy, are typically taken into account when evaluating the effectiveness of the EDM process15,16. However, it is also crucial to consider energy consumption and CO2 emissions in EDM processes to ensure the preservation of natural resources and the environment for future generations. The present investigation is specifically focused on analyzing the sustainable aspects of the EDM process applied to SS310 alloy. This analysis encompasses key measures of machining performance, as well as considerations related to environmental and economic factors. In order to enhance the sustainability of EDM, the research investigates the impact of electrode materials and machining variables.

The current paper is organized like this: Section "Literature review" offers an extensive literature review that delves into the machining performance and sustainability prospects of the EDM process. Section "Materials and methods" outlines the materials and methods employed in the experimental procedures. Section "Results and discussion" comprehensively discusses the results and findings derived from the experimentation. Section "Sustainability analysis using multi-criteria decision-making" presents the sustainability analysis of the EDM, considering the utilization of various electrode materials and machining variables. Finally, Section Conclusion concludes the research by summarizing the key findings and conclusions.

To address the need for sustainability in the manufacturing industry, this section highlights the gaps present in the existing literature regarding sustainability in the electric discharge machining process. Therefore, this section provides a thorough literature review of machining performance considering key machining variables and response measures. The sustainability of the EDM processes has been reviewed thoroughly.

Within the existing body of literature, the evaluation of the machining performance in the EDM commonly involves the analysis of various criteria, including but not limited to MRR, quality of the machined surface, and tool wear. Generally, it is hard to attain superior machining performance while producing delicate shaped impressions on the workpiece of hard-to-cut materials17. Therefore, researchers have tried to optimize the machining variables for various hard-to-cut materials to improve the conflicting nature response measures18 simultaneously. The electrode material plays a key role in establishing the machining performance among various machining variables. Hence, the electrode material is carefully selected while considering the workpiece material’s characteristics. Usually, electrical conductivity, thermal conductivity, melting point, erosion resistance, and wear resistance are considered when selecting electrode material18. Higher electrical conductivity and lower resistance of the electrode facilitate the flow of discharge current (I) to produce intense spark discharge at the electrode-workpiece interface. Moreover, the electrode materials should have higher wear resistance to spark erosion to withstand the intense heat generated during the spark discharge.

In a related study by Raza et al.19, the authors examined the machining of Al6061-SiC-7.5 wt% composite using three distinct types of electrodes: stainless steel, brass and copper. Their research findings indicate that the copper electrode emerges as the most favorable choice for simultaneously optimizing MRR, Ra, and EW ratio. Ahmed et al.18 conducted a study to assess the influence of electrode material on the surface characteristics of SS316L. The results revealed that the utilization of an aluminum electrode resulted in enhanced surface quality. On the other hand, the implementation of a brass electrode yielded higher surface microhardness. A study conducted by Maccarini et al.20 assessed the impact of electrode materials, specifically tungsten carbide and brass, on the machining effectiveness of Ti6Al4V grade 5 and AISI316L workpieces in the electric discharge drilling. Brass electrode works better than tungsten carbide electrode for MRR; however, tungsten carbide electrode has been shown to have lower EW.

In the analysis of the machinability of Ti-6Al-4 V alloy, Rahul et al.21 examined the performance of three different electrodes: tungsten, copper, and cryogenically treated copper. According to their findings, the copper electrode that underwent cryogenic treatment performed better than the other electrodes in terms of MRR, surface finish, and decreased EW. Şimşek et al.22 investigated the effects of different electrodes, including electrolytic copper, CuCo2Be, CuCr1Zr (as received), and CuCr1Zr with different aging treatments while machining SAE 1040 steel. Their findings revealed that CuCr1Zr electrode with 2–4 h of aging offered a superior MRR due to improved electrical conductivity. However, no significant effects of aging treatment of CuCr1Zr electrode have been observed on EW ratio. In the machining of Inconel 600, Ishfaq et al.23 conducted an analysis to investigate the impact of various electrode materials, including copper, graphite, aluminum, and brass. They concluded that copper and graphite electrodes demonstrated a higher MRR and lower EW ratio than brass and aluminum electrodes. However, it was noted that the use of graphite as an electrode resulted in a higher Ra when compared to other electrode materials, particularly when utilizing kerosene oil as the dielectric fluid. In addition to electrode material, the machining variables substantially impact the machining performance. Achieving a higher MRR necessitates the utilization of elevated levels of discharge energy parameters, such as I, Pon, SG, and DC. Conversely, selecting lower values of these parameters allows for better control over Ra and EW. As these response variables exhibit conflicting tendencies, it becomes crucial to optimize these parameters simultaneously while considering the characteristics of both the electrode and workpiece materials.

Sustainable electric discharge machining (SEDM) is a relatively new concept to conventional processes, and it not only focuses on productivity and quality but also considers environmental and economic perspectives. Li et al.24 prioritized surface quality as a prime indicator for sustainability analysis, followed by productivity, cost and environmental impact. In this regard, energy-efficient parameters are necessary to improve surface quality and productivity and minimize costs and environmental impacts25. Therefore, most studies have been conducted on efficient energy utilization in order to assess the sustainability potential of EDM. Regarding this matter, Zhang et al.26 presented magnetic field-aided EDM as a sustainable manufacturing approach. The objective was to enhance machining performance while minimizing EC and machining noise. They conducted a set of experiments utilizing machining variables such as Pon, Poff, and magnetic field intensity. Notably, the study revealed that Pon and magnetic field intensity significantly influenced EC and machining noise. The influence of I, Pon, and magnetic field intensity on energy efficiency and carbon emissions was examined by Ming et al.27. The analysis revealed that energy efficiency increased as I, Pon, and magnetic field intensity were raised. Additionally, a notable reduction in carbon emissions was observed when the discharge current was decreased and the magnetic field intensity was increased.

Wu et al.28 established sustainable EDM milling by utilizing a high-efficiency green pulse power source that produced more energy. A comparative analysis demonstrated that the energy utilization rate of conventional EDM milling was approximately 25%, whereas sustainable EDM achieved an impressive energy utilization rate of 95%. Ming et al.29 explored the effects of I, Pon, and DC on exhaust emission characteristics and energy efficiency per volume during the machining of Al 6061 and SKD 11. The study revealed that, in comparison to Pon and DC, I significantly influenced both energy efficiency and exhaust emissions. The impact of various machining variables, including I, Pon, open voltage, and DC, on machining noise and specific EC, was analyzed by Shastri and Mohanty30. The study additionally provided insight into how various electrode materials, including copper, tungsten, and copper-tungsten, affected these responses. The findings indicated that increasing the I, Pon, and open voltage significantly increased specific EC and machining noise. Furthermore, it was observed that copper electrodes exhibited the lowest EC but produced higher levels of machining noise compared to tungsten and copper-tungsten electrodes. The relationship between EC and surface integrity aspects, including Ra, surface topography, and spectral density analysis, was examined by Nieslony et al.31. In their study, Ra was correlated with machining time; however, machining time was measured in terms of EC. A direct relation was observed between EC and surface integrity.

Rao et al.32 conducted an analysis of the effects of magnetic field assistance and machining variables, including I, Pon, Poff, and open voltage, on EC and aerosol emissions. The study found that lower levels of I and open voltage contributed to reduced EC, while lower levels of I and Pon, along with intermediate levels of open voltage, resulted in lower aerosol emissions. Interestingly, the presence of a magnetic field decreased EC but increased aerosol emissions during the EDM process. It was also noted that the electrical conductivity of the electrode material influenced the energy efficiency. However, limited research has been conducted on the impact of electrode material on EC and its environmental implications in EDM processes. The main focus of this study is to investigate the impact of electrode materials (copper and brass) on various sustainability criteria. For each electrode material, the set of machining variables, including I, SG, Pon and DC, has also been optimized. These criteria encompass productivity indicators such as MRR and EW, as well as measures of machining quality such as surface roughness (Ra) and surface microstructural characteristics. Additionally, the study considers economic aspects related to machining and electrode costs and environmental factors, including the assessment of carbon emissions resulting from the consumption of discharge energy, dielectric, and electrode material.

This section discusses the workpiece and electrode materials used for the machining process. Experimental processes, including machining variables and response measures, are also discussed. The overall research methodology has been presented in Fig. 1.

Research methodology.

The high tooling costs involved with conventional machining typically make non-conventional machining procedures the preferred method for machining hard-to-cut materials. As a result, this study focuses on the electric discharge machining (EDM) of stainless steel SS310. This particular material is chosen for investigation due to its extensive range of applications, including fluidized combustor beds, radiant tubes, kilns, steam boilers, hangers for petroleum refining tubes, coal gasifiers with internal parts, thermowell, lead pots, burners, refractory anchor bolts, combustion chambers, muffles, retorts, annealing covers, cryogenic structures, and food processing tools33. A rectangular-shaped stainless steel SS310 plate having dimensions of 250 × 150 × 10 mm3 has been used as workpiece material for electric discharge machining. The chemical composition of the workpiece material (SS310) is shown in Table 1.

The selection of electrode material plays a crucial role in controlling the machining characteristics within EDM. The productivity and MRR are particularly influenced by the electrical conductivity of the chosen electrode material. Higher electrical conductivity supplies more I to the machining zone and removes more workpiece material by melting and evaporation. Thermal conductivity and melting point mainly define the EW during EDM. Higher thermal conductivity facilitates faster dissipation of heat generated at SG into the bulk of the electrode and prevents electrode material from localized overheating and melting. The electrode material’s higher melting point shows that it requires more heat for its erosion and wear and can withstand higher temperatures (at SG) without deteriorating. The hardness and thermal conductivity of the electrode material affect the workpiece’s surface properties. A higher hardness in the electrode material allows it to withstand wear and maintain sharp edges, leading to smaller and more localized sparking. Additionally, a higher thermal conductivity in the electrode facilitates the rapid dissipation of heat from SG, preventing localized melting of the workpiece surface. As a result, an improved surface finish is achieved. Copper and brass electrode rods with a 10 mm diameter and a 150 mm length were selected in order to assess the impact of electrode materials in SEDM. These materials were selected based on their superior productivity and quality characteristics, as reported in previous research19. The selection of the electrode material depends on its availability, cost, and machining characteristics. The thermal, electrical and physical properties of the selected electrode materials have been provided in Table 2.

NEUAR CNC-M50 electric discharge machine has been used to perform experimental trials. Kerosene oil has been used as a dielectric medium between the electrode and workpiece. Tween 80 (Polysorbate 80) is a hydrophilic nonionic surfactant employed in the dielectric fluid to regulate the deposition of carbon on the machined surface. To optimize the machining performance in SEDM, various machining variables, including I, SG, Pon, and DC, were taken into consideration. All the machining variables and constant parameters are provided in Table 3. The evaluation of SEDM’s machining performance was based on productivity indicators such as MRR and EW, surface quality measurements encompassing Ra and microstructural attributes, and EC. For MRR, machining time has been recorded for a 1 mm depth of cut of the workpiece in the case of both copper and brass electrodes. The mass of the specimens before and after machining using a digital weighing scale having a sensitivity of 1/100 of a gram. The total volume of the workpiece removed was calculated by dividing the mass difference by the density of the workpiece material. The total volume computed was then divided by the total machining time to calculate the material removal rate using relation 1.

where MWB and MWA are the mass of the workpiece before and after machining while t is the total machining time and ρ depicts the density of the workpiece material.

Electrode wear after each experiment was calculated by measuring the mass difference of electrodes before and after the machining using a weighing scale with a sensitivity of 1/1000 of a gram. The relation used in measuring electrode wear has been provided in Eq. 2.

where MEB and MEA are the mass of the electrode before and after each experiment.

The surface roughness of the machined surfaces was measured at three distinct points using a portable surface roughness tester (MITUTOYO Surftest SJ-310), and the average values were considered as the final Ra value for each experiment. The cutoff length of 4 mm was considered for Ra measurement. Moreover, the surface quality and characteristics of the machined surfaces were analyzed using scanning electron microscopy (SEM) at low and high energy parameters for both copper and brass electrodes.

The energy consumption of each experiment has been computed by recording the voltage and current induced during the machining process. Furthermore, the machining time was also recorded for each experiment. The energy consumed during each experiment was calculated by multiplying the current, voltage, machining time and duty cycle using relation 3.

where V and I are the voltage and current values, t is the machining time of each individual experiment, and \(\eta\) is the DC.

where Pon and Poff are the pulse on and pulse off times.

The machining cost of each experiment was calculated based on the energy cost, electrode cost, dielectric cost, labor cost, and machine depreciation cost. For the energy cost, the total energy consumed was multiplied by the unit electricity price in the Pakistani rupees. Moreover, electrode and dielectric costs were calculated based on the electrode material consumed during each experiment. The labor and machine depreciation costs for each experiment were mainly computed on the basis of the total machining time.

The environmental impact of the machining process has been analyzed by computing the overall carbon emissions produced during each experiment. For the comparative analysis, carbon emissions of each experiment have also been computed for both copper and brass electrodes. For the comprehensive assessment of the carbon emissions of the machining experiments, the emissions from energy consumption, dielectric consumption, and electrode wear/consumption wear were computed. For the carbon emissions from energy consumption, the electricity mix of Pakistan was considered.

A Taguchi L9 array was employed to conduct a comparative performance analysis of two different electrode materials, considering four machining variables. 9 experiments were performed using 4 variables for each electrode material; hence, a total of 18 experiments were conducted in this study. In order to ensure a fair comparison, the same set of experiments was repeated for both electrodes. The composite desirability function approach has been used for multi-criteria decision-making for the sustainability analysis of the machining process.

The examination of machining performance, cost, and environmental impact based on experimental data is the main focus of the section that follows. The experimental design matrix based on results obtained from the pilot trials is presented in Table 4.

In this section, the impact of various machining variables, including I, SG, Pon, and DC, on MRR, Ra, EW, and EC during the machining process is discussed. Additionally, the study explores the effects of different electrode materials, specifically copper and brass, on these machining parameters. Similar parametric effects/trends have been observed for both copper and brass electrodes. Based on the observations in Fig. 2, it is evident that the average MRR experiences an increase from 1.78 to 2.67 mm3/min as I raised from 4 to 12 A for the copper electrode. At 4 A, discharge current intensity is insufficient to effectively remove a larger quantity of workpiece material. However, a substantial enhancement in MRR is observed when I increased to 12 A. This increase in MRR is mainly due to the production of intense spark discharges at the interface region. High intensity spark discharges melt and evaporate the workpiece material and eradicate more material from the work surface. The investigation revealed that widening SG from 6 to 12 mu leads to a decrease in MRR, dropping from 2.51 to 1.83 mm3/min. This reduction can be attributed to the increased distance between the electrode and the workpiece, which reduces the intensity of the spark discharge channel, resulting in a smaller volume of work material being removed. On the other hand, as shown in Fig. 2, an increase in Pon from 15 to 45 µs enhances MRR from 1.75 to 2.66 mm3/min. This improvement is attributed to the prolonged duration of spark discharges, leading to a more efficient removal of work material. When spark discharges are produced for a longer duration, more material is melted and evaporated from the work surface. An increase in DC from 75 to 85% improves MRR from 1.92 to 2.29 mm3/min. An increase in DC primarily results in an extension of Pon and a reduction in the Poff. At higher values of DC, Pon is higher enough to melt more workpiece material; however, the Poff is relatively shorter and remains inadequate for removing the melted material by flushing. For this reason, the material removal rate increases by increasing DC, but this increment is not significant compared to other machining variables. A comparative analysis of electrode material shows that copper electrode offer higher MRR (2.67 mm3/min) than brass electrode (1.64 mm3/min). The higher MRR exhibited by the copper electrode can be primarily attributed to its superior electrical conductivity, which enables a greater supply of electric current to the machining zone. In contrast, the brass electrode possesses relatively lower electrical conductivity, resulting in inadequate MRR during machining. Moreover, copper has a significantly higher thermal conductivity (401 Wm-1 K-1) than brass (150 Wm-1 K-1), which means it can dissipate heat from the electric spark/plasma more efficiently. With brass, more heat energy builds up locally, whereas copper spreads it out, maintaining stronger spark intensities for longer durations. The sparking phenomenon for copper and brass electrode at specific time t depicts that copper removed more material than brass electrode due to intense sparking, as shown in Fig. 3.

Analysis of the mean effects of machining variables and electrode material on MRR.

Schematic illustration for the material removal process using (a) copper and (b) brass electrodes.

Figure 4 illustrates the impact of machining variables and electrode material on Ra. From the graph, similar patterns of the effects of machining variables have been seen for Ra. It can be observed that the increase in I from 4 to 12 A increases Ra from 4.62 to 6.34 µm while using the brass electrode. This phenomenon can be attributed to the rise in the intensity of spark energy with an increase in I. Intense and irregularly sized sparks irregularly remove work material, producing deep craters and contributing to the formation of valleys. Moreover, a large amount of the work material resolidifies from the molten pool on the work surface and generates irregular peaks. These nonuniform peaks and valleys result in increased Ra. It has been observed that Ra increased slightly from 5.11 to 5.26 µm when SG was increased from 6 to 9 mu. Smaller spark gaps produce lower Ra due to the localized erosion, which is more consistent and controlled. There are fewer chances of uneven sparking and melting/vaporization at the edges of craters formed on the machined surface. Further increase in SG (to 12 mu) raises Ra significantly (up to 6.06 µm). Larger spark gaps, on the other hand, result in wider and deeper craters due to less focused spark energy over the gap distance. Figure 4 shows that a short Pon (15 µs) results in a relatively lower Ra of 4.58 µm, which is mainly due to less heat accumulation and reduced thermal energy transfer to the workpiece. Increase in Pon from 30 to 45 µs raises Ra 5.26 to 6.59 µm. A longer Pon provides a higher amount of discharge energy to the machining zone, leading to increased melting and vaporization of the work material. As a consequence, a significant amount of material from the molten pool solidifies and accumulates on the work surface, ultimately resulting in an elevated level of Ra.

Analysis of the mean effects of machining variables and electrode material on Ra.

Like other machining variables, DC also has a direct relation with Ra. Increasing DC from 75 to 85% raises Ra from 5.0 to 5.87 µm. A lower DC (short Pon and long Poff) allows more time for the melted material to flush away before the next spark, leading to a smooth and clean machined surface. Higher duty cycles concentrate more energy in a smaller area, which generates excessive heat and causes non-uniform melting and evaporation. This produces uneven layers of resolidified material with deeper and narrower craters on the work surface, leading to a rougher surface texture than lower duty cycles. A comparative analysis reveals that, when utilizing the specified machining variable settings during EDM of SS310, the copper electrode provides a comparatively superior surface finish (3.36 µm) compared to the brass electrode (4.58 µm). The enhanced surface smoothness of the workpiece can be attributed to the higher electrical and thermal conductivity of copper in comparison to the brass electrode. These enhanced conductive properties facilitate the generation of stable and controlled spark discharges, leading to a uniform dispersion of discharge energy, which ultimately results in a better surface finish. Conversely, brass has a lesser electrical conductivity, implying that less energy is transmitted to the plasma channel when electrical discharge machining is performed. Moreover, brass has a lower thermal conductivity, leading to a greater heat build-up in the plasma channel. Instead of a concentrated localization, this causes a less even dispersion of spark discharges across the machined surface. Consequently, the brass electrode’s low thermal and electrical conductivities cause ineffective and erratic sparking as well as comparatively uneven craters and cavities on the machined surface. The surface texture produced by the copper electrode shows a relatively smooth surface with small and shallow craters, as shown in Fig. 5a. On the other hand, the brass electrode offers significantly higher peaks and deeper valleys on the machined surface of the workpiece, and the same phenomenon has been schematically illustrated in Fig. 5b. Owing to the lower melting, brass electrode face more wear during the machining which leads to inconsistent and irregular spark discharge. This results in uneven wear of brass electrode and ultimately transfers uneven material removal from the workpiece surface. Moreover, the lower electrical and thermal conductivities also result in uneven erosion of workpiece material due to erratic discharges.

Schematic illustration of the workpiece surfaces machined using (a) copper and (b) brass electrodes.

To gain insight into the surface attributes of the machining surfaces, scanning electron microscopy was performed at low, medium, and higher roughness values of machined surfaces for both electrodes, as shown in Fig. 6a–f. For this reason, the machined surfaces of Exp. No. 1, 4 and 7 have been chosen for morphological analysis. It can be seen that the low energy parameters (I = 4 A, SG = 6 mu, Pon = 15 μs, DC = 75%) offered a quite smooth surface with few cavities and craters while using the copper electrode as shown in Fig. 6a. This better surface is primarily due to the moderate sparking which removes workpiece material gently. Similarly, the brass electrode also offers a better surface finish using the same machining variables; however, the machined surface produced with the copper electrode is finer and offers a smaller and limited number of craters than the brass electrode, as shown in Fig. 6d. Machined surfaces with cracks, wider and shallow cavities with tiny sized redeposited material and craters have been observed at Exp. No. 4 (I = 8 A, SG = 6 mu, Pon = 30 μs, DC = 85%) using copper electrode (Fig. 6b). Figure 6e shows deeper cavities, cracks, globules and redeposited material on the machined surface generated by brass electrode using same machining variables. Higher energy parameters (I = 12 A, SG = 6 mu, Pon = 45 μs, DC = 80%) result in a poor machined surface, as shown in Fig. 6c,f. However, a relatively better-machined surface with shallow cavities, globules and a few debris particles has been obtained with the copper electrode (Fig. 6c). In comparison with copper; the brass electrode produces large-sized globules, cracks, and numerous redeposited particulates can be visualized on the machined surface while using same machining variables (Fig. 6f).

Scanning electron microscopic analysis of machined surfaces at Exp. No. 1, 4 and 7 using (a–c) copper and (d–f) brass electrodes.

Figure 7 depicts the contribution of different machining variables and electrode material on EW properties using copper and brass electrodes. It can be assessed that raising in I from 4 to 8 A increases EW from 0.334 to 0.394 g; however, this increment (0.521 g) is significant at 12 A using a brass electrode. The discharge current determines the amount of energy delivered during each discharge. As I increase, it generates greater thermal energy at the interface between the electrode and workpiece. This increased thermal energy not only facilitates the removal of workpiece material but also induces localized melting and vaporization of the electrode material, resulting in wear. Increasing SG from 6 to 12 mu reduces EW from 0.430 to 0.404 g, as shown in Fig. 7. SG affects the formation and collapse of the plasma channel during discharge. A larger SG requires a higher voltage to initiate the discharge, resulting in a limited and controlled discharge process. This controlled discharge can reduce the erosion of the electrode material, leading to reduced wear. Increasing Pon from 15 to 45 µs significantly raises the wear from 0.360 to 0.468 g of brass electrode. Pon directly impacts the thermal energy supplied to the electrode and workpiece interface during each discharge event. A longer Pon results in higher energy input, leading to increased localized heating and melting of the electrode material; hence, this increased thermal energy contributes to EW. DC also has a direct relationship with EW. Varying DC from 75 to 85% increases EW from 0.388 to 0.455 g (Fig. 7). DC directly affects the thermal energy transmitted to the electrode and workpiece interface. A higher DC (Pon is a greater proportion of the total cycle time) results in a longer duration of high-energy discharges and provides a short time for the electrode to cool down. This increased thermal energy input can lead to higher temperatures for a prolonged period of time and cause more significant localized heating, contributing to increased EW. A comparative analysis of EW shows that brass electrode yield more EW than copper electrode, as shown in Fig. 7. The melting point of the electrode material is one of the main reasons behind EW. The melting point of copper (1083 °C) is relatively higher than brass electrodes (940 °C). This means that copper electrode can withstand higher temperatures before melting or eroding. Brass electrods, on the other hand, have a lower melting point and can experience melting or erosion at lower temperatures. The lower melting point of brass can contribute to increased EW during EDM. The wear behavior of copper and brass electrodes is schematically illustrated in Fig. 8, which shows that the surface of brass electrode has higher erosion than copper.

Analysis of the mean effects of machining variables and electrode material on EW.

Schematic illustration of electrode wear for (a) copper and (b) brass electrodes.

The machining variables immensely influence EC in the EDM process, as workpiece material is removed by the electrical and thermal energies, which is a fundamental principle of EDM. An increase in I from 4 to 12 A leads to a notable escalation in EC, rising from 204.1 to 333.9 kJ when using the brass electrode, as depicted in Fig. 9. The discharge current determines the amount of electrical energy delivered during each discharge event. Increasing the I give more energy to the workpiece, resulting in a higher EC for the material removal process. Varying SG from 6 to 12 mu lead to reduce the EC from 302 to 238.3 kJ. A larger SG necessitates a higher voltage to maintain a stable discharge. This higher SG results in a lower I for the same energy input parameters. Moreover, fewer discharges are happening per unit of time, reducing the overall EC. Pon also has a direct relation and increases EC from 221.6 to 306.6 kJ with the increase in Pon from 15 to 45 µs. Pon directly contributes to the amount of energy delivered to the workpiece and electrode interface during each discharge. A longer Pon means that the discharge energy is supplied for a prolonged period of time, resulting in a higher energy input. EC also rises from 238.3 to 285.3 kJ, with the increase in DC from 75 to 85%. DC determines the portion of the discharge cycle during which the discharge is active. A higher DC, where Pon has a greater proportion of the total cycle time, allows the supply of more energy input. This can result in higher EC as more energy is delivered to the workpiece during the active discharge period.

Analysis of the mean effects of machining variables and electrode material for EC.

Figure 9 depicts the significant difference in EC of both copper and brass electrodes. It has been observed that copper electrode offers less EC throughout the experiment (for a 1 mm depth of cut) than brass electrode. Compared with the brass electrode, copper allows an efficient energy supply during the discharge process due to its higher electrical conductivity. As a result, using copper electrode can lead to lower EC as more electrical energy is effectively utilized for material removal. In contrast, brass has lower electrical conductivity, which leads to higher resistance to I flow. This increased resistance results in higher EC for the same machining conditions and parameters than copper electrode. Moreover, brass has lower thermal conductivity compared to copper, which might lead to increased EC, as the heat generated during the EDM process may not dissipate as effectively as it would with a copper electrode.

Machining cost analysis helps in estimating the cost of producing a machined part or component. Analyzing the machining costs allows manufacturers to identify areas where costs can be optimized and reduced. In this regard, optimization of the machining variables is crucial in order to minimize the cost. Therefore, this section analyzes the effects of different machining variables on energy cost, electrode cost, dielectric cost, labor cost and machine depreciation cost using both copper and brass electrodes. Energy cost refers to the cost incurred due to the energy consumed during the material erosion process. Electrode cost is the cost of the electrode material eroded during the machining; moreover, it also includes the cost of electrode material removed to obtain the fresh face of the electrode for the next machining experiment. After each experiment, 2 mm (across the length) of the electrode material was removed/machined to acquire a fresh face surface. The cost of dielectric is calculated by measuring the cost of the volume of the dielectric fluid consumed by evaporation during each experiment. Besides this, labor and machine depreciation costs are also analyzed with respect to the selected machining variables. Labor and machine depreciation costs are computed with respect to the machining time of each experiment. Unit values of different cost factors for the calculation of energy cost, electrode cost and dielectric consumption cost are provided in Table 5. Using experimental data and unit costs of different factors, the energy cost, electrode cost, dielectric consumption, labor cost and machine depreciation cost are computed.

By observing Fig. 10, it becomes evident that there is a direct correlation between energy cost and EC. An increase in I, Pon, and DC leads to higher machining costs due to the corresponding rise in EC. However, the increase in SG reduces EC, hence resulting in low energy costs. The analysis of mean values of costs depicts that the energy cost of brass electrode is relatively higher (2.83 PKR) than that of copper electrode (2.02 PKR). The main factor contributing to the higher energy cost is the inefficient energy supply, primarily resulting from brass’s lower electrical and thermal conductivity compared to copper electrodes. Additionally, the machining variables have an impact on EW due to variations in the amount of energy delivered to the machining zone. Higher levels of I, Pon, and DC, along with a lower SG, lead to an intensified energy supply that causes melting and evaporation of the electrode material from the machining zone. For this reason, high electrode cost has been observed on higher energy parameters than low energy parameters, as shown in Fig. 11. Owing to the variation in the melting point and electrical and thermal characteristics of copper and brass electrodes, the EW behaviour of both electrodes is significantly different from each other. Brass has a low melting point and electrical and thermal characteristics; therefore, higher EW has been observed. However, contradictory results have been observed in the case of electrode cost. The copper electrode yields a higher electrode cost of 5.54 PKR than the brass electrode (3.66 PKR), as shown in Fig. 11. It can also be seen that the machining variables also affect the dielectric consumption (Fig. 12). As discussed, higher levels of I, Pon, and DC, and lower level of SG supply intense energy to the machining zone. This intense energy also evaporates the dielectric fluid during sparking. Therefore, the evaporation of the dielectric fluid incurs the dielectric cost. The comparative analysis revealed that the usage of brass electrode resulted in significantly lower dielectric cost (22.28 PKR) than copper (5.203 PKR) as depicted in Fig. 12. It is primarily due to the supply of lower energy (in the case of brass electrode) to the machining zone, which remains inadequate to evaporate dielectric fluid. Due to less evaporation of the dielectric fluid, the cost of dielectric consumption remains lower than that of the copper electrode.

Analysis of the mean effects of machining variables on EC and energy consumption cost.

Analysis of the mean effects of machining variables on electrode material removed and electrode cost.

Analysis of the mean effects of machining variables on dielectric consumption and dielectric cost.

A distinct behavior of the labor cost and machine depreciation cost with respect to the selected machining variables has been observed in Fig. 13. It can be seen that the increase in I, Pon and DC speed up the material removal process due to the intensive energy supplied to the machining zone. This intensive energy minimizes the overall machining time and ultimately reduces the labor hours and machine operating time; hence, labor cost and machine depreciation costs are decreased. However, the increase in SG supplies less energy to the electrode and workpiece interface region; therefore, machining time increases to remove the specific amount of material. This increased machining time also raises the labor and machine depreciation costs. Comparative analysis of the electrode materials depicts that copper electrode reduces the labor cost (80.12 PKR) and machine depreciation cost (99.3 PKR) than brass electrode (129.4 and 160.4 PKR, respectively), as shown in Fig. 13. This decrease in cost is mainly attributed to the reduction in machining time owing to the better supply of energy to the machining zone. The improved supply of energy is mainly due to the better electrical and thermal conductivity of copper compared to brass electrode.

Analysis of the mean effects of machining variables on labor and machine depreciation costs.

Machining processes consume a significant amount of energy, which, in turn, supplies a considerable amount of carbon footprints for the environment34. In order to evaluate the carbon emissions generated from EC, it is necessary to calculate the carbon emission factor. For this reason, the power production in Pakistan comes from different sources (including hydro, natural gas, coal, furnace oil, nuclear and renewables), and their contributions to the total power production are provided in Table 6. The standard values of carbon emissions of each source are considered to compute the carbon emission factor of energy production in Pakistan. The carbon emission factor from Pakistan’s power production has been determined as 0.242 kgCO2 eq./kWh, and it was used to assess the carbon emissions resulting from the EC during each experiment. Moreover, dielectric fluid and EW consumption also result in an environmental burden. Therefore, the volume of the dielectric fluid was measured after each experiment, and the carbon emissions from the consumption/evaporation of dielectric fluid were determined using the carbon emission factor of the kerosene oil, as shown in Table 7. Carbon emissions of each experiment for both copper and brass electrodes have been computed by considering EW and material removed/machined (2 mm across the length) to attain the fresh face for each experiment. The carbon emission factors for copper and brass electrodes are provided in Table 7.

A mean effects analysis was conducted to examine the impact of various machining variables on carbon emissions resulting from EC. Figure 14 illustrates that increasing the levels of I, Pon, and DC leads to higher carbon emissions from EC. This is primarily due to increased electrical energy consumption at higher energy levels than the above-mentioned parameters. However, the increase in SG decreases the carbon emissions due to reduced energy supply to the machining zone. A relative analysis of electrode materials shows that carbon emissions from EC due to the usage of the brass electrode (13.72 g CO2) are higher than that of the copper electrode (9.80 g CO2), as shown in Fig. 14. Higher electrical and thermal conductivity of copper enables more energy-efficient sparking than that of brass. This directly translates to lower electricity consumption and reduced carbon footprint from EC. Figure 15 depicts the mean effects of the machining variables on the carbon emissions produced from the dielectric fluid (kerosene oil) consumption. Another observation reveals that the heightened levels of I, Pon, and DC result in the delivery of intense energy to the machining zone, leading to the evaporation of dielectric fluid. This evaporation process directly contributes to carbon emissions being released into the environment. Conversely, an increase in SG provides a lesser amount of energy to the machining zone, resulting in the evaporation of a lower volume of dielectric fluid and ultimately reducing carbon emissions. A comparative analysis of electrode materials demonstrates that the brass electrode results in lower carbon emissions (32.33 g CO2) due to the consumption of dielectric fluid as compared to the copper electrode (54.58 g CO2), as depicted in Fig. 15. It is because of higher electrical and thermal conductivities of copper than brass electrode which cause intense sparking and generate higher temperatures at the machining zone. This higher temperature vaporizes the dielectric fluid from the interface region; hence, carbon emissions due to dielectric fluid consumption are higher in the case of copper electrode.

Analysis of the mean effects of machining variables on carbon emissions from EC.

Analysis of the mean effects of machining variables on carbon emissions from dielectric consumption.

Figure 16 illustrates the impact of various machining variables on carbon emissions resulting from electrode erosion. The analysis reveals that an increase in I, Pon, and DC leads to an intensified supply of energy to the machining zone, resulting in greater erosion of the electrode material and higher carbon emissions. Conversely, an increase in SG reduces the supply of discharge energy, leading to a lesser amount of electrode material being melted and evaporated, ultimately resulting in lower carbon emissions. Analysis of carbon emissions due to electrode consumption in Fig. 16 describes a distinct behavior compared to Fig. 7 (showing the mean effects of EW), providing a comparative analysis of EW. As mentioned earlier, the wear of the brass electrode was found to be higher than that of the copper electrode. Consequently, it can be inferred that the carbon emissions associated with the brass electrode would be higher compared to the copper electrode. However, the analysis provides the carbon emissions of EW + 2 mm length of electrode material removed (to obtain the fresh electrode surface for the next experiment). As the production of 1 kg of copper releases more carbon emissions than 1 kg of brass, therefore, a distinctive behavior of the carbon emissions has been observed in Fig. 16. This is mainly due to the 2 mm length of electrode material removal for each experiment, which overcomes the effects of EW, and higher carbon emissions are obtained in the case of copper electrodes (5.07 g CO2). This is primarily due to the immense carbon emissions produced during the production of copper and brass, however, brass has a significant proportion (35 wt%) of zinc, which reduces the overall carbon footprints of brass production (Table 7).

Analysis of the mean effects of machining variables on carbon emissions from electrode erosion.

Machining processes often consume significant amounts of energy and resources, including raw materials, such as metals and cutting fluids, which can contribute to environmental degradation38. By evaluating EC and material usage, manufacturing firms can optimize operations, minimize environmental degradation, and promote resource conservation. Additionally, sustainable practices often lead to cost savings, improved efficiency, and compliance with regulations and stakeholder expectations. Therefore, this study first defines the criteria for the assessment of the sustainability potential of electric discharge machining as per investigations24. In this regard, productivity, quality characteristics, economic aspects, and environmental perspectives have been considered for the sustainability analysis. The MRR, which determines the machining rate, has been taken into account to evaluate productivity. Conversely, the quality of the machined specimens has been assessed based on Ra, where a lower Ra indicates higher quality. For the economic analysis, total costs (affecting machining rate), including energy cost, EW and surface removal cost, dielectric consumption cost, labor cost and machine depreciation cost have been considered. The environmental impact of the machining trials has been assessed through the carbon emission produced by the energy, electrode, and dielectric fluid consumption.

Sustainability is a multidimensional concept that requires a holistic perspective. Analyzing criteria individually may overlook the broader context and fail to capture the overall sustainability performance and implications of a decision. A comprehensive analysis that considers the interactions and synergies among criteria is crucial for effective sustainability decision-making. In situations where an increase in MRR may have a negative impact on quality characteristics, there is often a need to consider trade-offs within sustainability criteria. To address this challenge in multi-criteria decision making, the composite desirability function approach has been widely adopted. This approach involves transforming response values into desirability values using a desirability function that is not constrained to a specific range. According to Long et al.39, the range of desirable outcomes is from 0, which represents the least desirable, to 1, which represents the most ideal. A minimization function has been selected for Ra, total cost, and overall carbon emissions, whereas a maximization function has been selected for MRR. The weighted mean of all the desirability values is used to calculate the composite desirability, which is obtained after the desirability functions for each individual response have been calculated. In this particular study, all responses of both electrodes have been given equal weights when computing the composite desirability.

Through careful consideration of the trade-offs between response measures, a consensus has been reached to identify a single optimal solution that effectively balances productivity, quality characteristics, total cost, and overall carbon emissions. The normalized optimal solutions for MRR, Ra, total cost, and CO2 emissions (calculated against their actual optimal solutions) based on the composite desirability function approach for copper and brass electrodes have been presented in Table 8. Based on the highest value of the composite desirability function, solution 1 has been selected as the best optimal solution. The optimal solution 1 shows that the 34.49% MRR, 66.46% Ra, 58.44% total cost, and 64.62% overall carbon emissions with a composite desirability of 54.25% can be obtained using the copper electrode. Using copper electrode with optimal setting of machining variables (I = 4 A, SG = 6 mu, Pon = 30 µs and DC = 85%), the trading off results for response measures including MRR = 2.17 mm3/min, Ra = 3.11 µm, total cost = 223.69 PKR and overall carbon emissions = 85.42 g CO2 eq. It has been found that 40.62% MRR, 63.95% Ra, 62.77% total cost, and 61.22% overall carbon emissions having a composite desirability of 56.21% results using brass electrode can be obtained. The optimal settings of the machining variables for brass electrode are similar to the optimal setting of the copper electrode; however, the distinct values of response measures, including MRR = 1.39 mm3/min, Ra = 4.42 µm, total cost = 342.47 PKR and overall carbon emissions = 65.09 g CO2 eq. have been obtained. According to the comparison analysis, the copper electrode performs better than the brass electrode in terms of total machining cost, MRR, and Ra. However, when it comes to total carbon emissions, the brass electrode performs better in the ideal configurations recommended by the composite desirability function technique. Despite this, the brass electrode has a higher composite desirability than the copper electrode, suggesting that when MRR, Ra, total machining cost, and overall carbon emissions are considered simultaneously during multi-criteria decision-making, the brass electrode is a somewhat better alternative.

In this study, the sustainability potential of electric discharge machining (EDM) of SS310 alloy is examined by exploring the effects of electrode materials. Specifically, a comparative analysis is conducted using copper and brass electrodes, and the machining performance of these electrodes is assessed based on MRR, Ra, EW, and EC. For the sustainability analysis of the machining trials, total machining costs (energy cost, electrode cost, and dielectric cost) and carbon emissions due to energy, electrode, and dielectric fluid consumption have been considered. The present research has yielded the following conclusions based on its findings.

The adjustment of I and Pon has a notable impact on regulating MRR in electric discharge machining, as they play a significant role in its control and manipulation. These machining variables directly determine the intensity and duration of the discharge energy supplied during the process. However, the analysis showed that copper electrode offered a higher MRR of 2.67 mm3/min due to higher electrical conductivity aid in the efficient supply of discharge energy than brass electrode (1.64 mm3/min).

Optimal conditions for obtaining minimum Ra involve utilizing lower levels of I, Pon, and DC, along with a higher SG. This combination ensures a controlled and limited supply of energy to the machining zone, resulting in improved surface quality. Notably, copper electrode outperforms brass electrode, achieving a lower Ra of 3.36 µm. This can be attributed to copper’s higher electrical and thermal conductivities, enabling more stable and controlled sparking during machining.

EW can also be effectively controlled by adjusting I and Pon, as these variables mainly regulate the discharge energy responsible for causing wear on the electrodes. Comparative analysis of the electrode materials revealed that the brass electrode results in a higher EW of 0.334 g due to its lower melting temperature, which causes more erosion than the copper electrode (0.272 g).

Significant reductions in EC can be achieved by decreasing I and Pon in electric discharge machining. These machining variables play a crucial role in determining the supply of discharge energy to the machining zone. By effectively reducing the levels of I and Pon, the overall EC can be effectively restrained. Discharge energy can be efficiently supplied by using copper electrodes due to their high electrical conductivity and offer lower EC of 145.8 kJ than brass electrodes (204.1 kJ).

The energy cost, EW cost and dielectric consumption cost can be reduced by using lower energy parameters. However, lower energy parameters take a longer time for the machining, increasing the labor and machine depreciation cost and ultimately increasing the total machining cost.

In comparison with brass, copper electrode offers lower energy costs due to an efficient supply of energy, while it yields elevated EW cost due to the higher cost of pure copper metal. An efficient supply of discharge energy evaporates more dielectric fluid in the form of fumes, which results in higher dielectric consumption costs in the case of copper electrode. This efficient energy supply removes the workpiece material in a timely manner, reducing the machining time. As a result, it decreases labor and machine depreciation costs compared to using a brass electrode. However, the total machining cost using brass electrode remains higher due to the dominance of labor and machine depreciation costs.

The application of copper electrodes facilitates the efficient utilization of energy, resulting in lower carbon emissions compared to brass electrode. A higher supply of energy evaporates more dielectric fluid, which ultimately results in higher carbon emissions due to dielectric fluid consumption for copper electrode. As the production of copper has a severe environmental impact, its wear during machining also results in higher carbon emissions. While overall carbon emissions due to the usage of brass electrode are lower than those of copper electrode, this is primarily due to a significant contribution of carbon emissions from dielectric fluid consumption and EW.

Comparative analysis revealed that copper electrode outperform in MRR and Ra and in total machining cost, while brass electrode excel in overall carbon emissions. The multi-criteria decision-making based composite desirability function approach depicts brass as having a higher composite desirability of 56.21% than copper electrode (54.25%).

This study presents the comprehensive cost and environmental impact analysis of the EDM process; however, the economic and environmental impact of post processes, such as lubricant waste disposal, are not considered in this study. Future studies can be conducted on the comprehensive life cycle analysis of the EDM process, considering the manufacturing/production processes of the workpiece, electrode, dielectric fluid, reinforcement particles (if any), their transportations, and the final disposal phases.

The datasets used and analyzed during the current study available from the corresponding author on reasonable request.

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The authors appreciate the support from Researchers Supporting Project number (RSPD2024R702), King Saud University, Riyadh, Saudi Arabia.

Department of Mechanical Engineering, University of Engineering and Technology, Taxila, 47080, Pakistan

Abdul Hannan & Shahid Mehmood

Department of Industrial and Manufacturing Engineering, Faculty of Mechanical Engineering, University of Engineering and Technology, Lahore, 54890, Pakistan

Muhammad Asad Ali

Department of Data and Systems Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong

Muhammad Huzaifa Raza

The Sargent Centre for Process Systems Engineering, University College London, Torrington Place, London, WC1E 7JE, UK

Muhammad Umar Farooq

Industrial Engineering Department, College of Engineering, King Saud University, 11421, Riyadh, Saudi Arabia

Saqib Anwar

Department of Mechanical Engineering, Landmark University, Omu-Aran, Kwara State, Nigeria

Adeolu A. Adediran

Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa

Adeolu A. Adediran

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Abdul Hannan: Conceptualization, Data curation, Formal analysis, Investigation, Writing-review & editing. Shahid Mehmood: Supervision, Formal analysis, Resources, Project Administration. Muhammad Asad Ali: Conceptualization, Methodology, Formal analysis, Writing-original draft, Writing-review & editing. Muhammad Huzaifa Raza: Methodology, Formal analysis, Validation, Writing-original draft, Writing-review & editing. Muhammad Umar Farooq: Conceptualization, Writing-original draft, Writing-review & editing. Saqib Anwar: Formal analysis, Validation, Writing-review & editing. Adeolu A Adediran: Formal analysis, Writing-review & editing.

Correspondence to Muhammad Umar Farooq or Adeolu A. Adediran.

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Hannan, A., Mehmood, S., Ali, M.A. et al. Machining performance, economic and environmental analyses and multi-criteria optimization of electric discharge machining for SS310 alloy. Sci Rep 14, 28930 (2024). https://doi.org/10.1038/s41598-024-79338-7

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Received: 17 June 2024

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DOI: https://doi.org/10.1038/s41598-024-79338-7

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