Investigation on the Wire Electric Discharge Machining Performance of artificially aged Al6061/B₄C composites by Response Surface Method

Abstract

Present research work is focused on investigation of material removal rate in Wire-ED Machining (EDM) of artificially aged Al-6061/ B₄C reinforced composites with 2-6 wt.% in peak aged condition. Combined effect of B₄C and artificial aging at 100°C improved the hardness by 20 - 170% under as cast and artificially aged condition. Initially the wire EDM experiments are conducted on Al6061 alloy and then the process parameters such as current, pulse-on time (t_on) and pulse-off time (t_off) are optimized to obtain the high material removal rate (MRR). At optimized conditions test samples with various % of B₄C are machined to study their influence on MRR. The study revealed that current and t_off had a significant influence. MRR increased as current is increased and it decreased as t_off is increased. Maximum MRR at optimum settings, current : 5.53 A, T_off: 10 µs and T_on: 36.46 µs is 2.45 mg/min. Considering the limitation of the experimental set up the modified optimum settings (T_off: 10 µs, T_on: 30 µs and current : 5 A) resulted in average MRR of 2.39 mg/min with deviation of 0.20 mg/min. The study showed that there is no significant difference in MRR and the morphology of the machined surface with respect to test samples of different % of B₄C particles as reinforcement in Al6061 composite.

Keywords:
Wire-EDM; Artificial aging; Al6061/B₄C composite; pulse on time; pulse off time

1. Introduction

Aluminium alloy and its composites exist in a variety of light alloy matrices, mainly Mg, Al, and Ti, with continuous fiber, ceramics in particle, chopped fiber, or whisker form reinforcements. Aluminum and its alloys are commonly utilised as the matrix in aluminum-based composites. SiC and B₄C are the preferred reinforcements in these matrices, however other materials such as TiC, Al₂O₃, and B fibres have been frequently employed in the past¹. In recent years, these composites have mostly been used in aerospace, automotive, and marine applications. When compared to unreinforced matrix alloy systems, aluminum composites reinforced with SiC particles improve yield strength by up to 20%, have a lower thermal expansion coefficient, higher elasticity modules, and better wear resistance. When compared to other materials, B₄C reinforced aluminum composites are harder, tougher, more fracture-resistant, lighter in weight, have better fatigue strength, and have dramatically improved characteristics. Aluminum based composites are now replacing steel and aluminum alloy components (e.g., hydraulic cylinder, drive shafts etc.) in the field of automotive sector for weight reduction and wear resistance in essential components^2-7. The comprehensive literature shows that boron carbide (B₄C) is an alternative for composites reinforced with silicon carbide (SiC) due to better interfacial bonding with matrix alloy. It is reported that interfacial bonding between the Al matrix with B₄C is better than that of SiC reinforced composites^7-9. Mechanical properties of composites have improved due to uniform distribution of reinforcement and a good interface between matrix and reinforcement. SiC reinforced composites have lower strengthening effects than B₄C reinforced composites. Age hardening is the prominent heat treatment process used to increase specific strength of several aluminium alloys^1-3. The primary purpose of ageing treatment of these alloys (Al-Mg-Si) is to obtain a systematically growing enormous number of uniformly distributed fine intermediate precipitates (Mg₂Si) in the matrix. Improvement in mechanical properties like hardness, tensile strength, and wear resistance have been extensively studied under both as cast and heat-treated conditions. Machining of such reinforced composite is challenging due to hard and abrasive nature of reinforced particles. The major challenges are considerably high-power requirement, high surface roughness, poor machinability, high tool wear and tool costs^10-13. In view of this, the wire-EDM is suitable method for machining of electrically conductive materials. In this process, material is removed due to high frequency repetitive sparks which occur between workpiece and tool. This leads to localized raise in temperature in the spark gap which melt and vaporize the material. The circulation of dielectric, regulated the electrical discharge and take the debris of machining away¹⁴. In recent days, this process is used for production of nozzles, miniatured holes for cooling turbine blades, biomedical and micro-electro-mechanical devices¹⁵ and polishing of 3D printed parts¹¹. The polished 3D printed SS316L resulted in removal of defects such as porosity, the balling pits and voids. The settings to the wire-EDM process parameters show significant influence on MRR, surface roughness and kerf width. The high t_on create prolonged discharge and results in higher surface roughness. The smaller SiC of size 0.7–13 μm did not show considerable difference on the surface quality and also, they resulted in bigger kerf width and lower tool wear compared to generated by larger sized particles. Use of the multiwalled carbon nanotubes (1 g/L) in the dielectric fluid improved MRR by 75.42%, reduced roughness of the machined surface by 19.15% and recast layer thickness as well as other surface defects in machining of Nitinol shape memory alloy¹⁶. Studies of zinc coated copper wire showed that electrical parameters such as capacitance and voltage, and machining parameters such as feed rate exhibited prominent combined effect on the surface roughness and kerf-width¹⁷. In general, increase in current and t_on resulted in improving the MRR^18-21. The dielectric fluid mixed with conductive powder produced a stable and higher electric discharge resulting in improved machining performance²². However, a comparative study of electrode wear showed that a significant amount to material transfer occur by copper electrode compared to the graphite. The increase in t_on and current resulted in increase of electrode wear and surface roughness of Al (6351)-SiC-B₄C composite due to production of larger craters²³. Ramulu and Taya²⁴ investigated the EDM characteristics of Al/SiC_w composites and it was found that MRR and surface roughness were higher for SiC_w 15% reinforced composite. The current is found significantly influence the surface finish and the effect of voltage as well as t_on was insignificant²⁵. Also, the percentage of ceramic reinforcement and t_on were found to be significant on surface finish and kerf width. The higher reinforcement content in the matrix material reduce the machining speed²⁶. Sushant Dhar et al.²⁷ developed a model for predicting MRR, tool wear rate and over cut for EDM of Al–4Cu–6Si alloy–10 wt.% SiC_P composites. Bassam Khan et al.²⁸ investigated the effect of T_on, T_off, wire feed rate and its tension, voltage, current and fluid pressure on surface roughness obtained on Ti-6Al-4V Grade-5 alloy. Study showed that cryogenic machining resulted in improving the machinability. The settings to the process parameters such as current, T_on, T_off, spark gap voltage showed significant influence on surface roughness of the cut surface.

Rahul Davi et al.²⁹ made a detailed review of effect of EDM process parameters on machining and also investigated the effect of tool geometry on the machining characteristics of SiC powder mixed hybrid metal matrix composite by EDM for drilling purpose. It was found that both material removal and tool wear rate increased with increase in current and the duty-factor for electrodes of cylindrical and conical geometries due to higher spark energy. Comparatively, the hollow cylindrical copper tool produced higher MRR compared to solid conical tool by 33.79%.

Machining of particle reinforced aluminum composite by traditional techniques shows challenges such as micro-cracks, pits formation, voids, high tool wear-rate and embedment of fractured particles on the cut surface. The machining quality greatly influence the performance of material in applications. Few of these challenges can be solved by wire-EDM. Literature show that there is a lack of information on the effect of B₄C particles in Al6061 composite with respect to MRR and its surface morphology during wire-EDM. This paper investigates the effects of crucial parameters on MRR, such as current, t_on, and t_off, and develops optimal settings to enhance productivity in terms of MRR and establish regression model to predict MRR by using response surface method. Further, the effect of wt.% of B₄C particles upto 6% on machining is also investigated.

2. Methodology

2.1. Preparation of B₄C particles for fabrication

B₄C particles are cleaned with distilled water in an ultrasonic agitator to cleanse its surface as well as to remove sedimented fine particles. Agitation process is performed 4 times for 10-15 min with distilled water. Water is to be decanted after each agitation and fresh water is to be used for the next stage. After cleaning the reinforcement particles with distilled water, it is to be cleaned once again with acetone by ultrasonic agitation. Acetone is then decanted and powder particles are dried. To eliminate volatile compounds, B₄C particles were preheated at 250°C/2 h. Particle agglomeration will be formed if B₄C is preheated above 300°C because of formation of boric oxide (B₂O₃) layer. Preheating B₄C particles removes surface impurities and improves wettability of the reinforcements³⁰.

2.2. Preparation of Al6061-B₄C composite

Table 1 shows composition of matrix material (Al6061) and Table 2 shows properties of Al6061 alloy and B₄C reinforcements. Figure 1a, b shows fabrication process of test samples. The reinforcement particles of size 35-40 μm (400 Mesh) are procured from Boron Carbide India limited, Mumbai. Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray spectroscopy (EDAX) of B₄C were used for the present work shown in Figure 1c, d. Al6061 billets are melted in a graphite crucible using a 5 kW electric resistance furnace, and the melting process is allowed to continue until a consistent temperature of 750°C is reached. Scum powder (small quantity) is added to the melt to remove floating slag. By adding dry hexachloroethane (C₂Cl₆-10gms) tablet molten melt is degassed³¹.

Table 1
Composition (wt.%) of Al6061.

Material	Si	Fe	Cu	Mn	Zn	Ti	Mg	Cr	Al
wt.% (Actual)	0.50	0.55	0.25	0.14	0.24	0.12	0.95	0.20	Bal.
wt.% (Standard)	0.40 - 0.80	0.70 Max.	0.15 –0.40	0.15 Max.	0.25 Max.	0.15 Max.	0.80 –1.20	0.04 –0.35	Bal.

Table 2
Properties of Al6061 alloy and B4C reinforcements.

Properties	Al6061	B4C
Hardness (HB 500)	30 BHN	3000 kg/mm2 (30 GPa)
Poisson’s Ratio	0.33	0.207
Elastic Modulus (GPa)	70-80	480
Density (g/cc)	2.7	2.52

Figure 1
(a) Stirring process (b) Pouring of molten metal into pre-heated die c) SEM micrographs of B₄C reinforcements d) EDAX of B₄C reinforcements.

The melt is then allowed to cool to a semi-solid state at 600°C (just below the liquidus temperature). The preheated B₄C (2, 4 and 6 wt.%) is slowly introduced into vortex of molten metal developed during continuous stirring at 150-200 rpm for duration of 10 min. After mixing reinforcements in semisolid state, composite slurry is reheated and kept at 750°C and stirring is repeated for 10 min at 400 rpm to obtain uniform distribution of B₄C particles in the matrix. Melt is poured into preheated cast iron moulds which are maintained at temperature of 500°C. Artificial aging is performed on cast samples by solutionizing at 558°C/2 h, then quenching in demineralised water at 25°C. Now samples are artificially aged in furnace at 100°C/8 h to achieve maximum hardness³⁰. To measure hardness of alloy and composites Micro Vickers Hardness Tester, Model – MMT X 7A was used with 200 gmf load and 15 seconds dwell time. Before performing hardness test all the samples were polished using disc polishing system with a velvet cloth impregnated with diamond paste, so that oxide layer and other impurities produced during heat treatment can be removed. The average of a minimum of five near identical indentation readings are noted down for each specimen at different locations of the test samples.

2.3. Density measurement

The presence of porosity, as well as its size and distribution in the matrix, is critical in determining the mechanical properties of composites. Porosity levels should be minimum in order to obtain better performance in the applications. Porosity occurs due to formation of air bubbles which enter the slurry during the stirring process. Table 3 shows theoretical and experimental density values of Al6061 alloy and B₄C reinforced composites. It is observed that the maximum porosity in the test samples is less than generally acceptable levels of 2-4%^32,33 porosity of the cast composites and confirms the suitability of the test specimens with minimal casting defects for further investigations. Also, it is found that the porosity got increased with increase in B₄C addition to the matrix. This resulted in improvement in nucleation sites for strain hardening during age hardening process^3,6. From Table 3 it is observed that for varied wt.% of reinforcements, theoretical and experimental densities are close to one other. Density of composite is marginally lower than base Al6061 alloy matrix. Addition of reinforcement particle (B₄C) having lower density compared to that of matrix (Al6061) has led to decrease in overall density of composites.

Table 3
Density value comparisons of Al6061- B₄C.

Density (g/cc)	wt. % of B4C reinforcement
	0% (Base)	2%	4%	6%
Theoretical Density (ρthe)	2.70	2.6964	2.6928	2.6892
Experimental Density (ρexp)	2.6728	2.6541	2.6401	2.6174
Percentage Porosity	1.007	1.568	1.96	2.669

“The theoretical density is calculated by the rule of mixture as follows:

• Density of Al6061-B₄C composites is given by^32,33,

  • _{${\rho }_{Al6061-B4C}=Vo{l}_{fAl6061}X{\rho }_{Al6061}+Vo{l}_{fB4C}X{\rho }_{B4C}$}

Where, 𝜌_Al6061 = Density of Al6061 alloy (2.7g/cc)

𝜌_B4C = Density of B₄C (2.52g/cc)

Vol_{f Al6061}= Volume fraction of Al6061 alloy

Vol_{f B4C} = Volume fraction of boron carbide

Experimental values are calculated by weighing the sample and dividing it by volume of respective samples. Samples of 15 mm diameter and 20 mm height are prepared and volume is calculated. The experimental density value is calculated as follows”,

$${\rho }_{Exp}=Weightofsample/volumeofsample$$

The porosity percentage is given by:

$$\%Porosity=[({\rho }_T-{\rho }_{Exp})/{\rho }_T]X100\%$$

Where, 𝜌_T = Theoretical density and

𝜌_Exp = Experimental density

2.4. Experimental set up

Experiments were performed using a 2-axis (X-320 mm, Y-400 mm) computer numerically controlled wire-EDM made by Concord wire-EDM, India (Model: DK7732). Tool electrode made of molybdenum wire (diameter: 0.16 mm) is employed. As a dielectric fluid, a mixture of soft water and gel is employed. The controller has a resolution of 0.001 mm. Experimental set up is shown in Figure 2.

Figure 2
Experimental setup.

2.5. Design of experiment

Effect of process parameters such as wire speed, voltage, t_off, t_on and current on machining of Al6061-SiC composite was investigated by the authors earlier and these parameters were optimized^34,35. In this work the critical parameters such as t_on, t_off and current were chosen by setting the voltage and wire speed levels as constant. Table 4 shows the wire-EDM process parameters and their levels. These levels are chosen based on the confirmation experiments by the authors for machining of similar base metal with different reinforcing material. During the experiments, the specimen thickness and supply pressure of dielectric fluid were kept constant. The experiments are designed using L₂₀ response surface method using central composite design. The design consists of 3 factors, with total 20 base runs and two blocks. The Cube points were 16, Center points in cube 12, Axial points were 12 and center points in axial is 0. Two-level, Full factorials were used for designing the experiments with two replications as shown in Table 5.

Table 4
Wire-EDM process parameters and their levels.

Parameters	Unit	Level 1	Level 2	Level 3
Toff	µs	10	15	20
Ton	µs	30	40	50
Current	A	4	5	6

Table 5
Experimental plan.

Std Order	Run Order	Pt Type	Blocks	Current (A)	ton (ms)	toff (ms)
2	1	1	1	6	30	10
3	2	1	1	4	50	10
17	3	0	1	5	40	15
5	4	1	1	4	30	20
8	5	1	1	6	50	20
11	6	-1	1	5	30	15
15	7	0	1	5	40	15
9	8	-1	1	4	40	15
10	9	-1	1	6	40	15
7	10	1	1	4	50	20
20	11	0	1	5	40	15
18	12	0	1	5	40	15
19	13	0	1	5	40	15
6	14	1	1	6	30	20
14	15	-1	1	5	40	20
13	16	-1	1	5	40	10
1	17	1	1	4	30	10
4	18	1	1	6	50	10
16	19	0	1	5	40	15
12	20	-1	1	5	50	15
38	21	0	2	5	40	15
36	22	0	2	5	40	15
35	23	0	2	5	40	15
40	24	0	2	5	40	15
31	25	-1	2	5	30	15
27	26	1	2	4	50	20
30	27	-1	2	6	40	15
32	28	-1	2	5	50	15
28	29	1	2	6	50	20
33	30	-1	2	5	40	10
23	31	1	2	4	50	10
22	32	1	2	6	30	10
26	33	1	2	6	30	20
21	34	1	2	4	30	10
29	35	-1	2	4	40	15
39	36	0	2	5	40	15
24	37	1	2	6	50	10
37	38	0	2	5	40	15
34	39	-1	2	5	40	20
25	40	1	2	4	30	20

2.6. Measurement of MRR

Test samples are machined as per experimental design shown in Table 5. During machining, the MRR acquired for each trial is determined using the weight loss technique, as described by the Equation 1. A digital mass balance is used to determine weight of work piece before (W_i) and after (W_f) machining (accuracy: 0.001g). The machined sample surfaces is shown in Figure 3.

Figure 3
Wire-ED machined test samples.

$MRR=\frac{W_i-W_f}{t}$ mg/s (1)

2.7. Morphological study

Optical and scanning electron microscopy (SEM) is used for morphological study of test samples. Dispersion of reinforcement in matrix alloy is investigated using SEM (Model: JEOL JSM 840A). The samples are finely polished, buffed and etched with Keller’s reagent (1.0 ml-HF, 1.5 ml-HCl, 2.5 ml-HNO₃ and 95ml-H₂O) to identify B₄C reinforcement in the matrix. The morphology of the wire-ED machined surface is studied using Inverted metallurgical microscope (Model: IM 7000, Mitutoyo) at different magnifications.

3. Results and Discussion

3.1. Distribution of reinforcement in the test samples

The dispersion of reinforcements of various compositions (2, 4 and 6 wt. %) in the metal matrix is shown in Figure 4a-c. Figure 4d shows the mineral composition of the reinforced B₄C particle. This examination is critical due to the fact that the mechanical property of composite is significantly influenced by particle distribution. It is seen from the figure that there is uniform distribution of reinforcements in matrix. Also, SEM images clearly indicate that the test samples are free from particle agglomeration, and blow holes or air pockets. In addition, the surface also exhibits minimal porosity in all the test samples.

Figure 4
Dispersion of reinforcements in test samples Al6061 alloy with (a) 2% B₄C (b) 4% B₄C and (c) 6% B₄C composites (d) Mineral composition of the reinforced B₄C particle

3.2. The effect of process on MRR

Figure 5 shows the effect of current, t_on and t_off on MRR. It is observed that increase in current from 4 to 5 A increased MRR due to increase in spark energy (Es)^35,36. Higher the Es, more the material is melted and vaporized^37-39 leading to higher MRR. Further, increase in current beyond 5 A reduced the MRR after reaching a peak value in between 5 to 6 A. This indicated that, the increase in current beyond the peak current values did not yield the MRR significantly.

Figure 5
The effect of a) current on MRR b) ton on MRR c) toff on MRR.

Change in current form 4 to 5 A resulted in increase in MRR by 13.45%, but its change from 5 to 6 A increased the MRR by 8.40%. Further, the effect of t_on is shown in Figure 5b. It is noticed that MRR marginally increased when t_on is increased. Change in t_on from 30 to 50 μs resulted in increase of MRR by 3.54%. The energy (E) of each spark is given by E = t_on × I × V. In each spark cycle as the spark duration is more the spark energy produced is also more, resulting in melting of material with greater crater size. MRR is directly proportional to crater radius. Beyond 40 μs, MRR remains almost constant. This might be due to recasting of molten pool surrounding the craters as a result of the prolonged cycle period. The effect of t_off on MRR is shown in Figure 5c. Increase in t_off time from 10 to 20 μs resulted in decrease in MRR. Interestingly, increase in t_off from 10 to 15 μs resulted in a sharp decrease of MRR by 28.32%. But further increase in t_off from 15 to 20 μs showed slightly lower rate of decrease in MRR., i.e 18.19%. t_off is the duration of time at which capacitors gets charged during which no sparks occur. During this period deionization of the dielectric fluid also occurs which means the machining does not occur during t_off period³⁷. As a result, raising the t_off increases the cycle duration while lowering the spark frequency, resulting in a decrease in MRR.

3.3. Analysis of variance of MRR

Effect of process parameter on MRR is analyzed using ANOVA method to find effect of each control parameters. The significance of these parameters' effect are determined by conducting an F-test with a confidence level of 95% as shown in Table 6.

Table 6
ANOVA of MRR.

Source	DF	Adj SS	Adj MS	F-Value
Current	1	1.4268	1.4268	17.64
ton	1	0.0420	0.0420	0.52
toff	1	10.1235	10.1235	125.19
Current*Current	1	0.5076	0.5076	6.28
ton * ton	1	0.0090	0.0090	0.11
toff * toff	1	1.2149	1.2149	15.02
Current* ton	1	0.2029	0.2029	2.51
Current* toff	1	0.0062	0.0062	0.08
toff* ton	1	0.0031	0.0031	0.04
Lack-of-Fit	19	0.9190	0.0484	0.34

It is observed from Table 6 that 𝐹 calculated is greater than 𝐹(𝛼=.005,29) for the machining parameters such as current and t_off. Hence the effect of these parameters are highly significant, a small change in settings of current and t_off results in significant variations to MRR. But, F values of t_on is less than critical values i.e., F = 0.52, which indicate changes in settings of t_on 30 to 50 A do not significantly alter MRR. Considering the energy efficient usage, the lower settings of current i.e., 30 A is suggested as viable setting. Further, interaction effect of t_off* t_on, t_on x current and t_off x current is shown through surface plots in Figure 6a, 6b and 6c respectively.

Figure 6
Interaction effect of (a) t_off x current (b) t_on x t_off (c) t_on x current.

From the F test on these interaction effect it is seen that the interaction of t_on x t_off, t_off x current (pooled F values=0.12) is not significant and the variations to settings can be made independently. But the interaction between t_on x current has marginal influence on MRR. It means the effect of current on MRR changes with changes in settings of t_on and vice versa. The significance of the lack of fit is also tested through F-Test as shown in Table 6 and it is seen that its F values are less than the F critical values indicating its effect as insignificant.

3.4. Optimization of the process parameters

Response surface method is adopted for optimization of machining settings that result in higher MRR while wire-EDM of Al6061 alloy. The corresponding optimization plot of MRR is shown in Figure 7. From figure, maximum MRR is obtained by settings, current-5.53 A, t_on - 36.46 µs and t_off – 10 µs. MRR predicted at this setting is 2.45 mg/min. However considering the limitation in the settings of the experimental set up confirmation experiments were carried out at t_off – 10 µs, t_on - 30 µs and current-5 A which resulted in average MRR of 2.39 mg/min with deviation of 0.20 mg/min.

Figure 7
The optimization plot of MRR.

3.5. Regression modelling of MRR

A regression model is developed to establish relationship between process parameters (Ic: Current, t_on: Pulse-on time, t_off: Pulse-off time) and the response parameter MRR. Main effect, interaction effect and their squared terms of these parameters are considered in the regression modelling. The developed predictive model is given by Equation 2. The coefficients of determination (𝑅²) for this equation is 85.32%. Confirmation experiments within the range of operational parameters are used to assess the predicting accuracy of the regression model, that is, 10 µs ≥ t_off ≤ 20 µs; 30 µs ≥ t_on ≤ 50 µs; 4 A ≥ I ≤ 6 A. The distribution of residuals is shown in Figure 8a-d. It is seen from the Figure 8a that residuals are very close to line of fit and they show normal distribution as shown in Figure 8b. However, one of the test results show the large deviation which form the outlier data set. The scatter plot shown in Figure 8c show that residuals are distributed randomly over line of fit. These figures indicate the confirmation of model adequacy tests. Figure 8c show the standardized residual error of MRR for each experiment. It is observed that the outlier data set is due to the experiments at settings predicted by regression model and the experimental results.

Figure 8
The distribution of residuals a) linear plot b) histogram plot c) scatter plot d) residual over experimental trial.

$$\begin{array}{l}MRR=–2.27+2.670I_c+0.0623T_{on}–0.488T_{off}–\\ 0.2127I^2{}_c–0.000283T^2{}_{on}+0.01316T^2{}_{off}–\\ 0.00788I_c\times T_{on}–0.0028I_c\times T_{off}+0.00020T_{on}\times T_{off}\end{array}$$ (2)

3.5. The effect B₄C content on MRR

The Al6061 composite is reinforced with B₄C particles upto 6% and further, its wire - ED machinability with respect to material removal rate is determined by machining these test samples at established optimum settings i.e., t_off – 10 µs, t_on - 30 µs and current-5 A. Figure 9 shows the MRR obtained by Al6061 test samples with 0, 2, 4 and 6 wt.% B₄C particles. It is observed that there is slight decrease MRR in these test samples with B₄C particles, however, the decrease in MRR is not significant. The small variation observed in the Figure 9 is mainly due to heterogeneous nature of the composite material.

Figure 9
MRR of Al6061 alloy with 0% to 6 wt. % B₄C particle reinforced composite.

Further the morphology of machined surfaces is carried out on the samples machined at optimum conditions. Figure 10a-d shows the cut surfaces of 0 – 6% B₄C composite as seen by the optical microscope and the Figure 11a-d shows the SEM images which show the micro-structure of the wire-EDM Al6061 with 6% B₄C particle composite. It is observed that the machined surfaces are characterized by uneven surfaces. This is mainly due to repeated melting and solidification of the localized regions of the machining zone which is exposed to high temperature. However, no specific difference in the patterns of the surface morphology is seen on the machined surfaces with different % of B₄C particles as seen in these figures. Also due to sudden cooling of the molten pool during toff, the surface cracks were seen to be developed as shown in Figure 11b and c. Due to the movement of the travelling wire over the molten pool, the surface is also seen to be distorted and forming the wear tracks as seen these figure.

Figure 10
(a) - (d) Surface morphology of 0 to 6 wt.% B₄C particle reinforced composite by optical microscope.

Figure 11
(a-d) Surface morphology of wire EDM surface of Al6061-B₄C composite (6%).

As shown in Table 7, the hardness of the test samples increased with increase in wt.% of B₄C particles, resulting in larger dislocation densities during solidification due to thermal mismatch between matrix alloy and reinforcement. This causes significant internal stresses and mismatch strain, which have an impact on microstructure and mechanical properties of composites. Matrix deforms plastically to meet reinforcement particles' smaller volume expansion, resulting in greater dislocation density. Increased dislocation density result in greater resistance to plastic deformation and an increase in composite hardness^1-3. As-cast Al6061 alloy had a VHN of 60, but as-cast Al6061- B₄C (1, 2, and 3 wt.%) composites had 70, 75, 84 VHN respectively, whereas artificially aged Al6061 alloy and its composite samples show hardness of 75, 128, 136 and 144 VHN respectively. The presence of reinforcement and aging effect at 100°C resulted in improving the hardness of the test material by about 20-140% compared to Al6061 alloy. Because of the difference in thermal co-efficient of expansion between matrix and reinforcements, presence of harder reinforcements in matrix accelerates the ageing kinetics during artificial aging³. This may lead to surface cracks on the machined surfaces as seen in the Figure 10. Due to very high temperature involved in wire EDM process, it is observed that microstructure of the machined surfaces is distorted compared to unmachined surfaces.

Table 7
Hardness of Al6061- B₄C (0, 2, 4 and 6% wt.) as cast and peak aged condition.

	As cast condition (BHN)	Peak aged condition at 100ᴼC (BHN)
Al6061 alloy	60	95
Al6061- 2% B4C	70	128
Al6061- 4% B4C	75	136
Al6061- 6% B4C	84	144

4. Conclusions

This paper investigated the effect of crucial parameters such as current, t_on and t_off on MRR and determined the optimal settings to enhance MRR while wire-EDM of upto 6 wt.% B₄C particle reinforced Al6061 alloy. The data generated by this research is helpful in machining of drive shafts in aerospace and automobile industry for selecting the optimum process settings for machining of aluminum composites. The following conclusion are drawn based on the wire-EDM of upto 6 wt.% B₄C particle reinforced Al6061 alloy.

• SEM microstructural analysis reveals homogeneous dispersion of B₄C particles in alloy matrix and as compared to Al6061 matrix alloy, 20-40% and 60-140% increase in hardness is seen in as cast and aged samples at 100°C for a significant period of time.

• MRR was significantly influenced by process parameters such as current and t_off. With increasing current and decreasing t_off in settings, the MRR increased: 4 A ≥ I ≤ 6 A; 30 µs ≥ t_on ≤ 50 µs; 10 µs ≥ t_off ≤ 20 µs.

• The maximum MRR is predicted at optimum settings, current-5.53 A, t_on - 36.46 µs and t_off – 10 µs is 2.45 mg/min. Considering the limitation in the settings of the experimental set up the modified optimum settings (current-5 A, t_on - 30 µs and t_off – 10 µs) resulted in average MRR of 2.39 mg/min with deviation of 0.20 mg/min.

• Within the working range, regression models are created to predict the MRR (4 A ≥ I ≤ 6 A; 30 µs ≥ t_on ≤ 50 µs; 10 µs ≥ t_off ≤ 20 µs) with average 𝑅² - 85.65%.

• The addition of B₄C particles to Al6061 alloy up to 6 wt.% did not have a significant effect on the MRR and morphology of the wire EDM machined surface.

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Publication Dates

• Publication in this collection
  22 July 2022
• Date of issue
  2022

History

• Received
  11 Jan 2022
• Reviewed
  21 Apr 2021
• Accepted
  05 June 2022