Experimental investigation of effective parameters on productivity improvement of the EDM process for corrosion resistant metals

doi:10.21203/rs.3.rs-2061876/v1

Inconel 625 superalloy and stainless steel 304 are known for their significant corrosion resistance along with their high hardness and strength. Therefore, they are used in a wide range of industries, including oil and gas, nuclear, etc. Electrical discharge machining is among the most widely used processes for machining of these metals. However, this process has limitations, such as low material removal efficiency, high surface roughness, and the formation of a recast layer. Therefore, in this study, the effective parameters on increasing the material removal efficiency and reducing recast layer thickness are investigated. These parameters include the dielectric fluid, electrode material, discharge current, and pulse duration. After performing the test matrix, the effect of each of the input parameters on the material removal rate, surface roughness and thickness of the recast layer is evaluated using the ANOVA method. The results of this analysis showed that the type of dielectric fluid and the presence of silver oxide nanoparticles have a significant effect on output variables. When using sunflower oil fluid containing nanoparticles and the silver electrode, the recast layer and surface roughness are reduced, while the average material removal rate increases by 40% compared to the traditional mode. Also, due to the biodegradability of deionized water and sunflower oil fluids, the environmental sustainability of the process in this study is increased and while increasing productivity, it leads to the sustainable development of the EDM process.

Electrical discharge machining

Material removal efficiency

Surface roughness

Recast Layer

Electrical discharge machining (EDM) is one of the most applied processes in production of metal parts with high hardness and abrasion resistance. This process also has special applications in the molding and machining industry of parts with high sensitivity to shear forces and mechanical stresses [1]. Inconel 625 superalloy and stainless steel 304 while having the high hardness and abrasion resistance, due to their resistance to corrosion at high temperatures and resistance to fatigue and creep, is widely used in manufacturing parts needed in various industries, such as oil and gas, petrochemical, automotive, defense, etc. Therefore, EDM process is one of the best methods for machining of these metals [2].

Functional physics of the EDM process is such that two metal electrodes, one in the form of a machining geometry and the other in a machined part, are immersed in a dielectric fluid such as kerosene. By starting the device and sending electrical pulses from the power supply, an electric field is created at the closest distance between the two electrodes, which causes dielectric ionization and the formation of a plasma channel. Through this channel, electrons and ions are then exchanged between the electrode and the workpiece by high-frequency sparks, leading to surface melting of the workpiece and chip away. In this process, there is no contact between the electrode and workpiece, and sparks are formed at a small distance called a gap [3].

Due to the thermoelectric nature of EDM, which is based on sparking and surface melting, a phenomenon called recast layer occurs on the surface of the workpiece. The formation of this layer occurs in the period between the end and the resumption of the sparking current and causes the re-freezing of part of the molten material on the worked surface of the workpiece [4]. The formation of this hard and brittle layer reduces the material removal efficiency, increases the surface roughness, and creates defects such as cavities and surface cracks in the workpiece. In general, various parameters such as the pulse duration and the properties of dielectric fluid affect the formation of the recast layer. Therefore, correct adjustment of machining operational parameters as well as the use of scientific innovations play an important role in reducing the thickness of the recast layer, increasing the functional efficiency, and increasing the quality of the machined work pieces [5].

Numerous studies have been performed on investigation, optimization, and prediction of parameters affecting the increase of EDM efficiency and reduction of the recast layer [6]. In the work of Dong et al. water in oil nanoemulsion and kerosene were used as the dielectric fluid. Also, the intensity of the current and the pulse duration are operational parameters. The results of this study showed that due to the high thermal and electrical conductivity of ionized water relative to kerosene, the surface crack density and surface roughness rate improve when using this fluid [7]. In the work of Valaki et al. Jatropha Curcas vegetable oil and neem oil have been used as dielectric fluids. The results of this study showed that when using Jatropha Curcas oil and decreasing the pulse off-time, while increasing the material removal rate, the surface hardness of the samples also increases. Also, when using neem oil, the removal rate is 22% and the surface morphology is 17% improvement [8].

In the work of Shabgard and Khosrozadeh, the effect of combining different nanopowders in dielectric fluid on the performance of EDM process as well as output parameters such as material removal rate, surface roughness and integrity have been studied [9]. In one of the studies performed on Inconel 718 superalloy, the effect of machining parameters was investigated by adding copper nanoparticles to kerosene. The results of this study show that with increasing discharge current, the material removal rate increases, and the surface finish decreases, which of course is accompanied by a decrease in surface crack density. Also, with increasing the pulse on-time, the material removal rate decreases and the surface finish increases, which, of course, is accompanied by an increase in the surface crack density [10]. In the work of Kumar et al. by adding alumina nanopowder to dielectric fluid, the machining performance has been investigated. The results showed that the nanopowder-mixed dielectric medium gives better surface finish and higher metal removal rate as compared to traditional dielectric. also, atomic force microscopy (AFM) and field emission scanning electron microscopy (FESEM) investigation of the machined surface reveals that presence of microcrack, micro-hole and tensile residual stress decrease substantially during process [11].

In all the mentioned research works: 1. Often, the performance of machining has been evaluated by examining a new fluid, which has caused insufficient information about the simultaneous effect of other fluids on the performance of the process; 2. In the field of dielectric additive nanoparticles, aluminum oxide, graphite oxide and copper oxide nanoparticles are often used, which have almost the same function; 3. In most studies on the qualitative parameters of surface health, only the surface roughness has been investigated and the thickness of the recast layer has not been considered; 4. Most EDM machining research works have been done using copper or aluminum electrodes.

Therefore, in the present study in order to increase machining efficiency and reduce the destructive environmental effects of kerosene fossil fluid, the effect of the most important parameters affecting the output variables, namely material removal efficiency, surface roughness and thickness of recast layer, have been investigated. Finally, new input variables are introduced which, while increasing machining efficiency and quality of manufactured parts, reduce waste and increase environmental sustainability and facilitate sustainable development of the EDM process.

2.1 Workpiece materials and equipment

The workpieces used in this research are in the form of sheets with a thickness of 6 mm and include Inconel 625 and stainless steel 304. Chemical compositions of the two materials are shown in Table 1 and Table 2.

Table 1

Chemical composition of Inconel 625.
Element	Ni	Cr	Mo	Fe	Nb	Co
wt. %	60	20	9	5	3.8	1.2

Table 2

Chemical composition of ss 304.
Element	Fe	Cr	Ni	Mn	Si	C
wt. %	65	18	8	2	1	0.07

The dielectric fluid, as the interface between the tool and the workpiece, is responsible for facilitating the formation of the plasma channel as well as washing the arc site. Fluids used in this study include kerosene, deionized water, and sunflower oil. From each fluid, two simple species and combined with additive nanoparticles in the amount of 1.5 liters were prepared (Fig. 1). Silver oxide nanoparticles with dimensions of 50 nanometers were added at a rate of 5 grams per liter of fluid. A suction pump and a hand-made metal tub is used to inject and transfer each fluid to the location of the arc pool.

The electrode, as the interface between the power supply and the workpiece, is responsible for transmitting electrical and thermal current as well as establishing the sparking current. In this research, two materials, namely copper and silver, is used as electrodes. Silver, as the material with the highest coefficient of electrical and thermal conductivity, has the best properties as the electrode material. The use of this material is one of the innovation indicators of the present study. The copper electrode is a stepped rebar with a diameter of 12 mm and a length of 60 mm. In the case of silver electrode and due to the high cost of this material, a rebar with a diameter of 12 and a length of 25 mm is used. Also, for easier installation of this electrode in the tool holder, a sequence is considered for it (Fig. 2).

2.2 Experimental procedure

In this study to investigate the effect of six input variables, namely discharge current, pulse duration, workpiece material, electrode material, additive nanoparticles, and dielectric fluid type, on changes in three output variables, namely material removal rate, surface roughness, and reset layer thickness, Taguchi method and an L36 test matrix are used. The input variables and the values of each of them are listed in Table 3.

Table 3

Input variables and their corresponding levels.
No	Variable	Level 1	Level 2	Level 3
1	Discharge current	5	10	20
2	Pulse duration	100	200	450
3	Dielectric fluid	Kerosene	Sun oil	Water
4	Electrode material	Copper	Silver	-
5	Nano particle	Exist	Absent	-
6	Workpiece material	Inconel 625	Ss 304	-

After performing the experiments, the values of each output parameter are measured and recorded in Table 4. To ensure the validity of the experimental data as well as to check the repeatability of the experiments, each row of the test table is repeated twice and the average value is considered. The purpose of these experiments is to investigate the effect of input variables on the material removal rate, surface roughness and thickness of the recast layer. Thus, ANOVA method is used to evaluate the effects of the input variables on the experimental outputs.

3.1 Material removal rate

The material removal rate is one of the most important output variables of the EDM process and indicates the amount of material harvested per unit time. Increasing the value of this variable increases the machining efficiency and production speed of parts [12]. Material removal tests based on the Taguchi design table is performed on both Inconel 625 and stainless steel 304 and the results are listed in Table 4. Figure 3 shows the experiments setup for material removal when using copper and silver electrode.

Table 4

Results of material removal rate, surface roughness and thickness of recast layer.
Run	MRR (mg/min)	SR (µm)	Recast layer (µm)
1	20.50	5.38	9.25
2	28.26	6.75	11.57
3	12.75	4.48	5.75
4	20.47	5.48	9.22
5	28.24	6.98	11.59
6	12.73	4.46	5.76
7	23.92	6.98	12.58
8	11.03	5.48	6.98
9	16/31	7.85	11.12
10	13.86	2.95	4.62
11	23.76	5.12	8.79
12	33.02	6.18	11.15
13	11.84	4.05	5.73
14	19.76	6.35	10.22
15	27.67	6.98	12.35
16	11.83	4.07	5.70
17	19.74	6.45	10.20
18	27.62	7.03	12.38
19	14.46	5.75	10.15
20	21.74	6.85	12.63
21	9.96	4.79	7.28
22	21.08	5.38	12.42
23	9.31	4.47	6.52
24	15.52	6.79	10.72
25	25.02	5.34	11.12
26	11.16	3.83	5.45
27	18.91	5.83	9.58
28	24.25	6.08	11.85
29	10.69	3.85	5.65
30	17.98	6.58	10.42
31	12.60	2.67	4.55
32	21.22	4.88	8.68
33	30.05	5.48	11.05
34	20.58	4.39	8.35
35	29.98	4.98	10.75
36	13.51	3.58	5.25

Analysis of variance is performed to evaluate the effects of six input parameters on the material removal rate and the results are shown in Table 5. In this analysis, the error value is taken as α = 0.5. This means that with a 95% confidence level, parameters with a P-value of less than 0.05 are effective inputs and parameters with a P-value of greater than 0.05 are ineffective inputs. Therefore, the effective parameters on material removal efficiency from the most effective to the least effective are the type of dielectric fluid, addition of nanoparticles, electrode material, discharge current, pulse duration, and workpiece material.

Table 5

Analysis of regression for assessing the effects of input parameters on material removal rate.
Source	DF	SOS	Mean squares	F-value	P-value
Regression	6	0.0572	0.0037	2.26	0.143
Discharge current	1	0.0024	0.0024	1.67	0.218
Pulse duration	1	0.0020	0.0020	1.22	0.285
Dielectric fluid	1	0.0074	0.0074	4.65	0.043
Electrode material	1	0.0043	0.0043	2.79	0.115
Nano particles	1	0.0062	0.0062	3.85	0.095
Workpiece material	1	0.0012	0.0012	0.68	0.378
Error	2	0.0071	0.0011
Sum	8	0.0440

Figure 4 shows the effects of each of the six input parameters on the material removal rate. In part a, it is clear that by increasing the discharge current, the amount of heat energy transferred to the workpiece surface increases and thus, leads to an increase in the material removal rate. In part b, with increasing pulse duration, first the material removal efficiency increases and after passing the range of 200 µs due to unstable and non-uniform conditions, this rate decreases. In part c, due to the short breakdown voltage and the short pulse off time of sunflower oil, the durability of the plasma channel and effective sparking is increased, and the highest material removal rate is achieved. On the other hand, due to the higher thermal conductivity of ionized water than kerosene, energy wastage in ionized water is higher and thus, the material removal efficiency is reduced. This is in line with results reported in the literature [11]. In part d, due to the higher electrical and thermal conductivity of silver as compared to copper, the material removal rate of the silver electrode is higher than that of the copper electrode. In part e, it is evident that when adding silver oxide nanoparticles, due to the reduction of dielectric strength and expansion of gap distance and better gap washing, the material removal rate increases up to 40%. Part f shows that due to the lower melting point and higher thermal conductivity of Inconel 625 when compared to stainless steel 304, the material removal rate of Inconel is higher. This is in line with results reported in the literature [13].

3.2 Surface roughness

The surface quality of the machined parts is an important variable in the EDM process. One of the most important indicators for measuring surface quality is surface roughness. Reducing the surface roughness is considered to be a main goal in all machining processes. Increasing the surface roughness destroys the surface morphology of the workpiece and causes surface defects such as cracks and cavities. This phenomenon can reduce the mechanical properties and lead to the premature failure of the workpiece [14]. In this study, after complete execution of the material removal operation, surface roughness of the samples is measured based on Ra criterion using a Taylor Hobson surface roughness tester (Surtronic model) with an accuracy of 0.01 µm. The results are listed in Table 4. The results of analysis of variance of the variables affecting the surface roughness are listed in Table 6. The parameters affecting the surface roughness from the most effective to the least effective are type of dielectric fluid, additive nanoparticles, discharge current, electrode material, pulse duration, and workpiece material.

Table 6

Analysis of regression for assessing the effects of input parameters on surface roughness.
Source	DF	SOS	Means square	F-value	P-value
Regression	6	0.0720	0.0048	2.58	0.138
Discharge current	1	0.0056	0.0056	2.96	0.118
Pulse duration	1	0.0047	0.0047	2.42	0.269
Dielectric fluid	1	0.0118	0.0118	6.26	0.038
Electrode material	1	0.0062	0.0062	2.75	0.135
Nano particles	1	0.0112	0.0112	5.89	0.075
Workpiece material	1	0.0029	0.0029	1.63	0.465
Error	2	0.0065	0.0021
Sum	8	0.0606

Figure 5 shows the effects of each of the six input parameters on the surface roughness. In part a, it is clear that with increasing discharge current, the amount of energy and heat stress transferred to the workpiece surface increases and results in an increase in surface roughness. In part b, with increasing pulse on-time and due to decreasing pulse off-time, surface roughness increases at first, but then decreases due to unstable and non-uniform conditions. In part c, due to the high thermal conductivity and the expansion of the radius of plasma channel when using ionized water, the density of surface cracks and the amount of surface roughness are reduced. In addition, the emission rate of toxic and harmful gases is reduced when using ionized water compared to kerosene, and the environmental compatibility of the process is increased. This is in line with results reported in the literature [14]. In part d, it is proved that by increasing the electrical and thermal conductivity of silver compared to copper, sparks are more evenly distributed on the surface of the samples, which reduces the peak and vales of the surface and improves its morphology. Part e shows that the addition of silver oxide nanoparticles to the dielectric fluid leads to expansion of plasma channel and the sparking frequency is improved. In this case, the energy of the sparks and the intensity of electric field will have a more uniform distribution. Also, by reducing the fracture strength of the dielectric fluid, electrical discharge begins at larger gap intervals, which leads to better washing of the gap space and reduces the possibility of harmful pulses such as shortcuts, leading to reduced roughness and improved surface morphology. This is in line with results reported in the literature [14]. Part f shows that due to the higher density of Inconel 625 compared to stainless steel 304 and also its lower melting point and higher thermal conductivity, the surface roughness of Inconel 625 is higher than that of stainless steel 304.

3.3 Recast layer

Due to the thermoelectric nature of the material removal mechanism in the EDM process, a heat affected area is created on the workpiece surface. The most important part of this area that forms on the surface of the workpiece is called the recast layer. This layer is another indicator of surface health, which consists of the re-freezing of molten material on the surface of the workpiece. When molten material erupts out of the molten pool at the end of the pulse on-time, some of this material re-freezes in the form of bumps and surface appendages on the workpiece. As a result, a hard and brittle layer is formed on the surface of the workpiece, which has microcracks due to the non-uniformity of the forming phases. Therefore, the formation of the recast layer, in addition to reducing machining efficiency, causes surface defects and reduces the mechanical properties of the workpiece. Therefore, in order to increase the operational efficiency of the process and achieve the appropriate surface quality in the parts, the recast layer should be reduced as much as possible [15].

After completing the experimental design table, each sample is cut and prepared using the wire cut process. Then, by performing metallographic operations, including polishing, felting and etching, the samples are prepared for analysis using a Scanning Electron Microscope (SEM). The SEM tests are performed by a VP 1450 device manufactured by LEO - Germany. According to the results of ANOVA analysis, it can be stated that the parameters affecting the recast layer thickness from the most effective to the least effective are type of dielectric fluid, additive nanoparticles, discharge current, electrode material, pulse duration, and workpiece material. The results of analysis of variance of the variables affecting on the recast layer are listed in Table 7. Figure 6 shows the effects of each of the six input parameters on the recast layer thickness. Examples of SEM images of recast layers obtained in experiments are shown in Fig. 7.

Table 7

Analysis of regression for assessing the effects of input parameters on recast layer.
Source	DF	SOS	Means squares	F-value	P-value
Regression	6	0.0939	0.0063	3.26	0.143
Discharge current	1	0.0061	0.0061	3.79	0.115
Pulse duration	1	0.0049	0.0049	3.12	0.275
Dielectric fluid	1	0.0104	0.0104	6.26	0.041
Electrode material	1	0.0059	0.0059	3.65	0.125
Nano particles	1	0.0108	0.0108	6.78	0.068
Workpiece material	1	0.0026	0.0026	1.52	0.473
Error	2	0.0073	0.0023
Sum	8	0.0722

In Fig. 6, part a shows that the thickness of the recast layer increases with increasing discharge current. From the view of the impact mechanism, it can be stated that with the increase of discharge current and thermal energy on the workpiece surface, the volume of material removal increases. This phenomenon causes a larger volume of molten material to be harvested and frozen on the surface of the workpiece. In part b, with increasing pulse duration and due to decreasing off- time of sparks and lack of proper washing of the gap space, first the thickness of the recast layer increases and then decreases with decreasing material removal efficiency. This is in line with results reported in the literature [15]. In part c, as mentioned in the previous sections, sunflower oil fluid has the highest material removal efficiency and surface roughness, and deionized water has the lowest material removal efficiency and surface roughness. This has caused the deionized water fluid to have the lowest recast layer thickness and the sunflower oil fluid to have the highest recast layer thickness. This is in line with results reported in the literature [15]. In part d, it is evident that the silver electrode has a more uniform mechanism in material removal than copper and naturally has a smaller thickness in the recast layer. Part e proves that the addition of nanoparticles changes the electrical properties of the dielectric fluid and thus, reduces the spark delay time. This reduces the off-time of the pulses and thus reduces the opportunity for the molten material to re-freeze on the surface of the workpiece. Part f shows that due to the higher material removal efficiency of Inconel 625 than stainless steel 304 (the reasons for which were mentioned in the previous sections), the thickness of the recast layer in this material is greater than steel. This is in line with results reported in the literature [13].

In this research, in order to increase the material removal efficiency, the quality of machined parts and increase the environmental sustainability of the EDM process, the effects of six input variables, including discharge current, pulse duration, dielectric fluid, electrode material and additive nanoparticles, on Inconel 625 and stainless steel 304 were investigated. According to the experimental results and statistical analysis, when using sunflower oil fluid with silver oxide nanoparticles and the silver electrode, the material removal rate increases by an average of 40% compared to the traditional case. This improvement is 30% for stainless steel. As a result, these variables can replace the traditional input variables, namely kerosene dielectric and copper electrode. Analysis of surface roughness on the machined samples showed that ionized water fluid with nano particles and silver electrode has the lowest surface roughness. In this case, while achieving acceptable material removal efficiency, the average surface roughness is reduced by up to 100% compared to the traditional case. Investigation of the thickness of the recast layer in produced parts proved that in test conditions with the lowest surface roughness, the thickness of the recast layer is decreased. Therefore, the minimum thickness of the recast layer is obtained when using ionized water fluid with nano particles and silver electrode. It should also be noted that when using sunflower oil fluid with nano particles and silver electrode, while increasing the material removal efficiency by 40%, the thickness of the recast layer is reduced compared to traditional variables. Analysis of results proved that the EDM process with the new variables introduced in this study, while increasing the efficiency of material removal and surface quality indicators of machined parts, has a high compatibility with environmental indicators that leads to reduced emissions and toxic waste and facilitates sustainable development of EDM process.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Author contributions

All authors contributed to the study conception, design, material preparation, data collection and analysis. The first draft of the manuscript was written by Mohammad Reza Saberi, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Experimental investigation of effective parameters on productivity improvement of the EDM process for corrosion resistant metals

Status:

Version 1

Abstract

Figures

1 Introduction

2 Experimental Investigation

2.1 Workpiece materials and equipment

2.2 Experimental procedure

3 Results And Discussions

3.1 Material removal rate

3.2 Surface roughness

3.3 Recast layer

4 Conclusions

Declarations

References

Status:

Version 1