Experimental Investigation of Wire-EDM Machining of Low Conductive Al-SiC-TiC Metal Matrix Composite

Abstract

The application of metal matrix composites (Al-SiC-TiC) in aerospace and defense industries have surged in the areas of hull safety, aviation fins, and closure units. The close to ideal solution for generating powdered mixture availing ball milling, for processing of a metal matrix composite of size 24 × 24 × 5.95 cm³ and composition of 75% Al, 10% SiC, and 10% TiC weight composition is 10:1 ball weight ratio, ball size of 8 mm, rotation speed of 250 rpm, and milling time of 4 h. The powdered mixture is compressed to pellet, sintered for two hours, and further silver coated in a physical vapor deposition setup to surge its electrical conductivity for ease of material removal. To obtain a perfect fit and finish, wire electrical discharge machining cycle has been carried out to machine the component under deionized water and oil + wax + paraffin dielectric mediums in 8 A peak current, 0.45 µs pulse on time, and 45 pulse off time as close to ideal solution, obtained by the technique for the order of preference by similarity to the ideal solution (TOPSIS) analysis. A surge is ascertained in kerf width, material removal rate, and surface roughness in oil + wax + paraffin environment in correlation with deionized water by 0.99–12.78%, 0.18–33.97%, and 2.15–36.86% respectively. The surface morphological study indicates a 32.28%, 42.57%, and 45.73% surge in residual compressive stress, surface roughness and corrosion resistance in oil + wax + paraffin dielectric medium in correlation to deionized water.

1. Introduction

Materials availed in the defense and aerospace industries are made of high strength Al-SiC composites for disparate applications, corresponding to hull safety, closure units, aviation fins, etc. [1]. The material fabricated is taken due to consideration for colossal stresses, hardness, and surface wear for rough terrain applications [2]. Being on the higher grade of hardness for composites pertaining to these applications, cutting techniques availed in the conventional cycle falls short to a large extent. In order to overcome the same, unconventional techniques, classified on the basis of removal of material, i.e., mechanical, chemical, thermal, etc., are availed to address the issue and also in turn ensure high levels of accuracy and precision values are obtained in the final product [3]. In correlation to the conventional cycle, the unconventional methods provide curtailed delamination and cutting forces in machining of the composites [4].

Scientists and researchers have performed various cutting operations availing mechanical erosion (abrasive water jet and ultrasonic erosion) [5,6,7], thermal erosion (electrical discharge machining, wire electrical discharge machining, and electron beam melting, laser cutting) [8,9,10,11], and chemical erosion (chemical erosion and electrochemical cutting) [12,13] for composites of varied natures. Though each of them are significant in achieving desired results, wire-electrical discharge machining (WEDM) [14] supersedes in the aspects of achieving high quality cutting and keeping it economical in perspective of cutting operation costs. Other cutting techniques, of abrasive water jet to laser cutting have a limitation of cutting thickness of the specimen and the economics of cutting is magnified by ten times in comparison with the WEDM method [5,15]. In terms of economics of machining, chemical or electrochemical erosion techniques provide cost effective methods, but they are also susceptible to damage of the workpiece in terms of accuracy due to the predominant factor of overcut and surface modification (corrosion: factor) [12].

In the WEDM technique, material is removed by thermal energy dissipation occurring between the tool (wire) and the workpiece produced by a factor of controlled discharges [14]. A dielectric medium (air, water, oil, etc.) is disposed into the machining cycle to flush out the machined material, again varied by the discharge control unit [15]. For engineers to avail WEDM substantially higher in comparison with other unconventional operations, as indicated in Figure 1 corresponds to simple profounding reasons, viz., the nature of machining is independent of the workpiece material (conductive in nature), thickness of the specimen, and economical and accurate cutting cycles [16,17,18]. These enhanced features makes the machining of high end steels, super alloys (Ni, Al, and Ti based) and metal matrix composites easier in correlation to other unconventional and conventional techniques [17,18,19].

Material removal rate (MRR) and roughness of the surface (R_a: average factor) are the most prominent characteristics of the WEDM process, which distinguishes the process along with the factors associated with the machining cycle and the dielectric availed for conducting the machining operation [14]. Two disparate types of dielectrics are availed, i.e., organic and inorganic based on the requirement and feasibility of the process [16]. These dictate the flushing factor in the machining cycle and play an important role in the final output delivered by the cycle of WEDM cutting [14,17]. Experiments were carried out to study the optimization of electrical discharge machining (EDM) parameters peak current, pulse time (on/off) with respect to the roughness form [16]. Statistical attributes corresponding to machining parameters of WEDM were carried out in correlation to surface roughness [17]. WEDM process parameters and its effect on machining of Titanium alloys were carried out using neural techniques [20]. An empirical understanding of the method was obtained and investigated with respect to the variables of cutting in WEDM technique [14]. Alumina ceramic cutting of WEDM was established empirically in correlation to the roughness factor [21].

Each condition of optimization and relations carried out provided a significant outlook to the WEDM process, but a major lacking point existed in the independent relationships of process factors with respect to responses and a major vector discrete outlook to the problem was missing [15,20]. Disparate replicas adopting multi criteria decision making methods have been availed to study the drilling of titanium alloys of higher order by scientists by the availing EDM cutting method [22,23,24,25,26]. Out of which multiattribute selection, Grey relational analysis (GREY), ELimination Et Choice Translation REality (ELECTRE), Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR), technique for the order of preference by similarity to the ideal solution Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), etc., found large applications in the manufacturing and industrial sector to resolve an optimized vector plane with minimal complexity. Out of which TOPSIS found its footing owing to less complexity and establishment of the Euclidean distance from the ideal solution [13].

Though researchers have carried out disparate techniques to establish relationships between parameters corresponding to WEDM cutting for various alloys and composites, a limited amount of research is carried out in machining of metal matrix composites (Al based), and to the best of the authors’ knowledge, no work has been carried out with respect to machining of the Al-SiC-TiC metal matrix composite by availing unconventional techniques. In this present work, ball milling is carried out to fine grain the powders of Al, SiC, and TiC to fine grain (nano) size, for which an optimized value is obtained for sintering and preparation of metal matrix composite. To make the composite conductive, a physical vapor deposition experiment is carried out to obtain a silver coating on the surface layer. Further experimental investigation of WEDM parameters is carried out in correlation to MRR and R_a by availing deionized water and asphalt wax based oil as dielectrics. An in depth characterization is carried out with respect to the surface morphology, residual stress, and corrosion factor to provide an in depth understanding of the machining cycle with respect to the dielectric effects. The optimized plane for ball milling and WEDM technique is obtained by availing a suitable statistical tool with low complexity and calculation at a rapid pace. 2. Materials and Methods 2.1. Machine Specification

The experiments were conducted using a Smartcut 2530 WEDM setup (Ratnaparkhi, Nashik, India), whose specifications are listed in Table 1.

The WEDM machine (Ratnaparkhi Smartcut 2530 WEDM setup, Nashik, India) is considered to be an indispensible tool in the area of unconventional machining, which avails a simple vertical wire under tension as the electrode controlled by a CNC for cutting disparate shapes, contours, and sizes. The system involves a main worktable, on which the workpiece is clamped, an auxiliary table, and wire driving mechanism as indicated in Figure 2.

The mechanism involves the movement of tables in Cartesian coordinates (X-Y) driven by DC servo motors. The electrode wire is in continuous motion through the workpiece and is ably supported under tension between a pair of wire guides placed at opposite ends of the workpiece, and this continuous motion is carried out by a wire fed spool and collected at the take up spool [15,20]. The lower wire guide is completely stationary but the upper guide movement is ably supported by a U-V table (auxiliary unit), which is displaced based on the lower guide. The upper guide is also repositioned vertically along the Z-axis by moving the quill. A schematic representation of the WEDM machining process is indicated in Figure 3.

To create a thermal flux between workpiece and the continuous wire electrode, a series of electrical pulses are generated by the pulse generator, to enhance the electro erosion of the workpiece material. As the process precedes, depending on the contour of the machining cycle, the workpiece table (X-Y movement) is displaced along a predetermined path controlled by the CNC unit. As the machining cycle occurs, the cutting zone and area of machining is flushed continuously in the presence of deionized water and oil–wax–paraffin (OWP) as dielectrics to ensure, no debris occurs along the surface. In order to prevent ionization of water due to electric pulses, an exchange resin is present in the distribution system to maintain conductivity [18].

2.2. Workpiece Material

For a wide scale industries ranging from aerospace and electronics research, Al-SiC find its relevance to applications in aircraft bodies and chip making components. The main associated drawback of the same lies in the forte of machining, which is cumbersome in the conventional cycle due to its supreme hardness of being composite in nature [5,10,12].

The addition of TiC to the Al-SiC composite is attributed on the fact of curtailing the factor of resistivity, thereby causing a surge in conductivity to make it more apt for the WEDM machining cycle. Additionally, the addition of TiC component surges the hardness parameter of the composite drastically. The surge in the hardness factor and drop in resistivity is reported in Table 2.

In order to obtain a perfect ratio for the component to form a composite of size 24 × 24 × 5.95 cm³ (6 samples overall), the methodology indicated in Figure 4 is followed. Figure 5 indicates the process equipment availed in the formation of the composite.

2.3. Decision Making Method (Multicriteria Analysis) for the Ball Milling Operation

An L₂₇ orthogonal array set of experiments are conducted as indicated in the methodology of Figure 5, for ball milling experiment and tabulated in Table 3 to obtain the right mixture for the composite on the basis of composition weight in order to obtain right physical and chemical properties of the composite.

To identify the close to ideal solution for the right mixture of composition of the making of the metal matrix composite Al-SiC-TiC, the technique for the order of preference by similarity to the ideal solution (TOPSIS) is availed for which factors are given precedence based on SIMOS weighted criteria method. The order of precedence of factors is tabulated in Table 4. The methodology availed for TOPSIS evaluation is depicted in Figure 6, for whose statistical complexity is minimal in correlation to other multicriteria methods [13]. The TOPSIS data for the ball milling experiment is tabulated in Table 5.

The ball milling parameters of the 10:1 ball weight ratio, ball size of 8 mm, rotation speed of 250 rpm, and milling time of 4 h was close to ideal factors to make a composite, of 75% Al, 10% SiC, and 10% TiC weight composition. The powdered mixture was compacted to a pellet in a square die, pressurized to 8–9 tonnes, and further sintered at a temperature of 500 °C for a duration of two hours and placed in the furnace for 24 h to attain room temperature. Slow cutting rates, and uneven machining was observed for the fabricated composite when machined availing the WEDM process, due to the minimal conductivity factor of the Al-SiC-TiC composite. To overcome this, silver paint was coated over the sample surface for a thickness of 8 microns and placed in physical vapor deposition chamber and heated for 150 °C for 45 min duration. Composite plates formed as indicated in Figure 7, are further machined availing the WEDM cutting cycle.

L₂₇ orthogonal array experiments are conducted for WEDM cutting of Al-SiC-TiC composites in two disparate dielectric mediums, i.e., deionized water and oil + paraffin + wax. For the process evaluation, peak current (I_p), pulse on time (µs), pulse off time (µs), kerf width, material removal rate (MRR), and surface roughness (R_a) were considered as factors and responses for the WEDM machining process respectively by keeping wire tension constant at 26 N. The statistical experimental data are tabulated in Table 6 and Table 7 for disparate dielectric mediums. Furthermore, the TOPSIS analysis with its weighted criteria is indicated in Table 8 (SIMOS criteria), Table 9 and Table 10 respectively. The responses for WEDM, kerf width, MRR, and R_a were obtained by metallurgical microscope, calculating cutting speed, sample thickness, and Talysurf contact type surface roughness instruments.

3. Results and Discussion The WEDM of Al-SiC-TiC is carried out in two disparate dielectric mediums whose close to ideal solution were 8 A peak current, 0.3 µs pulse on time, and 45 pulse off time. 3.1. Composite Structure

An X-ray diffraction was carried out as indicated in Figure 8, after the metal matrix was processed before the metal cutting operation was lugged out to study the chemical composition and overall phase orientations of the composite. The presence of Al-SiC-TiC content in disparate samples indicates uniformity in the processing of the samples for WEDM conditions.

3.2. Effect of WEDM Responses in Correlation to Factors of Machining

The Al-SiC-TiC samples were machined availing to the WEDM machine, as indicated in Figure 9.

From Table 11 and Figure 10, it is observed that there was a surge of kerf width, material removal rate, and surface roughness in an oil + wax + paraffin environment in correlation with deionized water by 0.99–12.78%, 0.18–33.97%, and 2.15–36.86% respectively. The MRR value in the WEDM machining cycle is given as the product of kerf width, cutting speed, and thickness of the sample. The cutting speed was found as the inverse of the cutting time measured during the experiment cycle [16].

It is ascertained from Figure 10 and Table 11, for both the cases of dielectric medium with a surge in T_on, T_off, and peak current the MRR rate improved drastically. This is attributed to the surge in energy of the single pulse discharge directly proportional to Ton [17]. In the case of dielectric medium of oil + paraffin + wax, an increase in the vaporization and melting in the cutting zone was ascertained. This can be attributed to the surge in gradient heat in the machining zone in the OWP dielectric cutting medium in correlation to deionized water [18].

The deionized water dropped the temperature significantly as T_off surged, causing a drop in surface roughness factor in correlation to OWP dielectric. Minimal debris solidification was ascertained in the Al-SiC-TiC surface layer due to the presence of deionized water as the melted part was washed away from the machining zone [21]. The presence of Ti and Al acted as a rebounding elemental part around the region of debris, which led to uneven machining as the rebounds induced a compressive factor opposite to the tensile residual stress due to the melting phenomenon occurring in the WEDM machining of Al-SiC-TiC [22]. In the case of a drop in T_off an insufficient pulse off time factor occurred causing a colossal curtailment in reionization of water (deionized), which led to erratic patterns in the machining cycle and curtailed the servo movement of the operating cycle. Though for the MRR, the value was higher in the OWP dielectric medium, it also caused an upsurge in the surface roughness factor, which aids in surface morphological properties of the machined component [23]. From Figure 10, it is ascertained that with the surge in feed rate, kerf width dropped significantly [21]. Lower feed rate provided a higher kerf width. A drop in kerf width ensured better accuracy in the machining composite sample, but the economics of the machining cycle were affected with an increase in cutting time of the sample. An optimal value correspondingly was carried out to ensure a balance in the accuracy of the machined sample and the accuracy of the wire electro discharge machining cycle. Additionally, pulse duration and peak current surge had a corresponding effect on the kerf width and MRR [23]. An increase in the peak current, corresponded to higher kerf width as the intensity of latent heat in the cutting zone surged drastically.

3.3. Surface Morphology

The presence of the silver coating acted as an adhesive layer inducing electrical sparks between the Al-SiC-TiC composite and the wire electrode. The silver coating also played a dual role of being a conductive-sacrificial layer, which was removed during the WEDM cycle. Figure 11, indicates the surface of the Al-SiC-TiC composite machined under deionized and OWP dielectric mediums. The SEM micrographs indicate a surge in the fine coarse grains aspect of the surface around the machining zone of OWP dielectric medium with an increase in the peak current value (ideal value being on the colossal side). This resulted in a surge of surface roughness of the WEDM machined Al-SiC-TiC composite [14].

The factor of roughness in the presence of OWP dielectric surged drastically, due to the latent heat being higher as indicated in the cross sectional view figure of kerf width. With the kerf width increase, large craters inside the surface were formed during the removal of material and with a simultaneous surge in the energetic pulse values a higher surface roughness factor was induced on the machined WEDM sample in correlation to the deionized water dielectric medium [21]. The factor of roughness was controlled with the amount of material removal and also the pausing time (T_off) as T_off surged the gap and ensured the flow of debris is smoother as a drop in the latent heat of fusion was ascertained in the machining zone [16].

3.4. Residual Stress

The residual stress measurement was carried out by the PANalytical X-Pert Pro materials research unit, and corresponding SEM images indicated were obtained by JSM-6610LV (JEOL, Akishima, Tokyo, Japan). The factor of residual stress in the OWP surged by 32.28% as indicated in Table 12 and Figure 12, in correlation to deionized water, as this is attributed to the presence of lower coarse grains in the surface of WEDM machined component as indicated in Figure 13 [24].

As the gradient heat was high in the OWP dielectric medium, the latent heat of fusion acting on the surface induced fine grains along the surface of the machined composite. A peak shift was experienced in the OWP dielectric medium machining of the composite in correlation with deionized water indicating a microstrain surge causing a dislocation density upsurge, which aids in the increase of the compressive residual factor [24]. With the surge in the density factor along the machined surface, curtailment was ascertained in the average size of the WEDM machined Al-SiC-TiC composite sample, which indicates a surge in the residual stress factor [25,26]. Additionally, aluminum being the major phase particle, the intermetallic phases formed cause a surge in the factor of residual stress at disparate WEDM machining conditions [27,28,29,30].

With a surge in the factor of T_on an upsurge of residual factor (compressive) is observed, as the slope between d-spacing and sin²ψ surges where the negative value showcased a compressive factor aided by the difference in the slope between both the dielectric mediums. This factor indicates a higher degree of interaction at the machining zone of parameters associated with WEDM machining [24]. Peak current plays a vital role in the relative effect of residual stress, by having a direct relationship with plastic deformation and temperature transformation gradients [16]. The factor of cooling by the dielectric induces a factor of compression and sparks generate the tensile residual stress factor inside the composite. The presence of pulse time off controlled the factor of tensile stress (residual) and keeping it minimal during the WEDM cutting cycle surged the occurrence of compressive stress factor in the material [14]. The plastic deformation induced the compressive residual factor in the presence of OWP as a dielectric medium, but in the case of deionized water due to continuous removal of thermal gradient at the zone of machining, a surge was witnessed in the nature of tensile residual stress factor along the WED machined Al-SiC-TiC composite surface [27]. In the case of a compressive residual factor, individual elements of the composite underwent expansion and contraction thereby causing a volumetric difference in the component, but as the composite internal hardness was colossal for Al-SiC-TiC, the material resisted the change in volume of the surface hindering the growth of dislocation, causing a barrier of fine grained structure [21].

3.5. Topographical Study

The topographical area of the WEDM machined zone was carried out by AFM (atomic force microscopy) for two disparate mediums of WEDM cutting of Al-SiC-TiC composites, as depicted in Figure 14 and corresponding roughness factors are tabulated in Table 13 [24].

The drop in surface roughness was ascertained in the dielectric medium of deionized water, by 42.57% in correlation to the OWP dielectric medium of WEDM cutting of the Al-SiC-TiC composite. The curtailed surface roughness was attributed to the reduction of crater formation during the deionized water machining availing WEDM cycle [25]. The surface roughness factor and waviness increase was also attributed to the variation in melting temperatures of TiC (3165 °C) and Al-SiC (2643 °C), which caused erratic fine grain disorientations in the WEDM machined composite under the OWP dielectric medium. The analysis holds significance to comprehend the deviations for applications requiring high tolerance values of the composite application [29,30,31].

3.6. Corrosion Analysis

Polarization curves (anodic in nature) are depicted in Figure 15, and their respective corrosion rate parameters are listed in Table 14, for two disparate mediums of WEDM cutting of Al-SiC-TiC composites.

A drop in the corrosion rate by 45.73% was ascertained in the OWP dielectric medium in correlation to deionized water [24]. The corrosion resistance surge ascertained in the OWP dielectric medium WEDM sample was attributed to three reasons. The presence of the residual factor (stress: compressive) aids in the formation of the passive barrier, thereby increasing the barrier potential for corrosion to occur [26]. The presence of high barrier potential elements of Al, TiC in the composite is further aided by the surge in roughness occurring in the OWP dielectric medium, causing a drop in the pitting potential for corrosion to take place [28,29]. A drop in the interatomic spacing due to the compressive residual factor causes further refinement in grain size along the surface, augmenting the passivation barrier inherently surging the corrosion resistance of the OWP dielectric WEDM sample [30].

4. Conclusions A research study was carried out to study the wire electrical discharge machining of metal matrix composite. The metal matrix composite was fabricated, and further machined under two different dielectric mediums, for whose major experimental findings are:

(1) The close to ideal solution for generating powdered mixture availing ball milling, for processing of a metal matrix composite of size 24 × 24 × 5.95 cm³ and composition of 75% Al, 10% SiC, and 10% TiC weight composition was the 10:1 ball weight ratio, ball size of 8 mm, rotation speed of 250 rpm, and milling time of 4 h. The powdered mixture was compressed to a pellet, sintered for two hours, and further silver coated in a PVD setup to surge its electrical conductivity for ease of material removal.

(2) The WEDM of Al-SiC-TiC was carried out in two disparate dielectric mediums (deionized water and oil+wax+paraffin solution) and close to the ideal solution for both the mediums were 8 A peak current, 0.3 µs pulse on time, and 45 pulse off time.

(3) A surge of kerf width, material removal rate, and surface roughness was ascertained in the oil + wax + paraffin environment in correlation with deionized water by 0.99–12.78%, 0.18–33.97%, and 2.15–36.86% due to increased vaporization and melting in the cutting zone causing a gradient heat difference between both the dielectrics. A surge in T_on, T_off, and peak current the MRR rate improved drastically. This is attributed to the surge in energy of the single pulse discharge.

(4) The deionized water dropped the temperature significantly as T_off surged, causing a drop in the surface roughness factor in correlation to oil + wax + paraffin dielectric. Minimal debris solidification was ascertained in the Al-SiC-TiC layer due to the presence of deionized water as the melted part was washed away from the machining zone, and indicating better morphology of the finished cutting surface in correlation to the oil + wax + paraffin dielectric.

(5) Material removed in the presence of the oil + wax + paraffin dielectric was substantially high in correlation with deionized water and in addition the presence of Ti and Al in the metal matrix composite acted as a rebounding elemental part around the region of debris, which led to uneven machining as the rebounds induced a compressive factor opposite to the tensile residual stress due to the melting phenomenon occurring in the WEDM machining of Al-SiC-TiC.

(6) The SEM micrographs indicate a surge in the fine coarse grains aspect of the surface around the machining zone of the oil + wax + paraffin dielectric medium with an increase in the peak current value (ideal value being on the colossal side), indicating a surge in roughness factor.

(7) The factor of roughness in the presence of oil + wax + paraffin dielectric surged along the kerf width, as the latent heat experienced in the cutting zone was higher in correlation to deionized water. With the kerf width increase, large craters inside the surface were formed during the removal of material aided by a simultaneous surge in the energetic pulse values inducing a higher surface roughness factor on the machined WEDM composite sample.

(8) The factor of residual stress in the oil + wax + paraffin dielectric medium surged by 32.28%, attributed to the presence of lower coarse grains in the surface of the WEDM machined component along with higher gradient heat, inducing fine grains along the surface, indicating a drop in the average grain size along the surface, aluminum forming an intermetallic phase, causing a dislocation density upsurge and additionally witnessing a peak shift in correlation to deionized water.

(9) The drop in surface roughness was observed in the dielectric medium of deionized water, by 42.57% in correlation to the oil + wax + paraffin dielectric medium of WEDM cutting of the Al-SiC-TiC composite. The curtailed surface roughness was attributed to the reduction of crater formation during deionized water machining availing WEDM cycle.

(10) The presence of the residual compressive stress factor, induced higher surface roughness, drop in interatomic spacing augments the formation of passivation barrier causing a drop in corrosion rate of 45.73% in the oil + wax + paraffin dielectric medium in correlation to deionized water for machining of the Al-SiC-TiC composite.

Figure 1. Application of unconventional machining for high hardness materials.

Figure 2. Wire electrical discharge machining setup and cutting action.

Figure 3. Wire electrical discharge machining process.

Figure 4. Methodology for processing of the Al-SiC-TiC metal matrix composite.

Figure 5. Process equipment in processing of the Al-SiC-TiC metal matrix composite.

Figure 6. Technique for the order of preference by similarity to the ideal solution (TOPSIS) methodology for ball milling and wire-electrical discharge machining (WEDM) cutting.

Figure 7. Processed Al-SiC-TiC metal matrix composite plates.

Figure 8. Processed X-ray diffraction of the metal matrix composite structure Al-SiC-TiC.

Figure 9. WEDM machined Al-SiC-TiC under close to ideal conditions using deionized water and oil + wax + paraffin as dielectric mediums.

Figure 10. Graphical comparison between WEDM cutting of Al-SiC-TiC in deionized water and oil + wax + paraffin dielectric mediums.

Figure 10. Graphical comparison between WEDM cutting of Al-SiC-TiC in deionized water and oil + wax + paraffin dielectric mediums.

Figure 11. Surface morphology of the wire electrical discharge machined Al-SiC-TiC metal matrix composite.

Figure 11. Surface morphology of the wire electrical discharge machined Al-SiC-TiC metal matrix composite.

Figure 12. XRD plot and residual stress analysis of wire electrical discharge machined Al-SiC-TiC metal matrix composite surface.

Figure 13. Surface morphology of Al-SiC-TiC wire electrical discharge machined zone in 5000× magnification.

Figure 14. Atomic force microscopy image of the wire electrical discharge machined Al-SiC-TiC metal matrix surface.

Figure 14. Atomic force microscopy image of the wire electrical discharge machined Al-SiC-TiC metal matrix surface.

Figure 15. Corrosion data analysis for wire electrical discharge machining of the Al-SiC-TiC metal matrix composite under deionized and oil + wax + paraffin dielectric mediums.

Machine Tool
Machine Tool	2530 Z-motorized
X, Y axis travel	250 mm × 300 mm
Maximum workpiece size	400 mm × 500 mm
Maximum taper cutting angle	10 degrees on 80 mm job height
Wire diameter	0.2 to 0.25 mm (Brass)
Max cutting speed	70 sq. mm/min (Job height 100 mm)
Max dry run speed	100 mm/min
Max Z height (mm)	200 mm
Max workpiece weight	300 kg
Control Panel SC 01
Control Mode	CNC close loop with compensation for X, Y U, V open loop
Simultaneously controlled axis	X, Y, U, V
Control Panel Size (L × W × H)	650 mm × 647 mm × 1675 mm
Minimum input command (increment)	0.001 mm
Interpolation function	Linear, Circular
No load voltage, V0	140 V
Servo reference voltage	65–75 V
Power requirement	415 V
New Feature	Online offset correction possible

Rockwell Hardness Data
Composition Weight (%)			Rockwell Hardness (HRB scale)			Average HRB
Al	SiC	TiC
80	20	-	25	25	25	25
75	20	5	33	31	33	32.33
70	20	10	45	44	42	43.67
Resistivity Data
Composition Weight %			Resistivity (Ω cm)			Average Ω cm
Al	SiC	TiC
75	20	5	0.3	0.32	0.28	0.3
70	20	10	40	45	50	45
65	20	15	910	890	900	900

S. No.	Weight Ratio of Balls to Powder	Balls Size (mm)	Rotation Speed (rpm)	Time (h)	Composition (Weight %)			Grain Size (nm)	D50 (nm)	SSA (m2/g)
					Al	SiC	TiC
1	5:1	6	150	4	65	10	5	29.4	2786	0.212
2	5:1	6	150	4	70	15	10	37.5	3581	0.175
3	5:1	6	150	4	75	20	15	31.4	2614	0.254
4	5:1	8	200	5	65	10	5	24.1	1618	0.415
5	5:1	8	200	5	70	15	10	19.4	1854	0.484
6	5:1	8	200	5	75	20	15	21.4	1715	0.462
7	5:1	12	250	6	65	10	5	16.5	1391	1.071
8	5:1	12	250	6	70	15	10	18.4	1379	1.045
9	5:1	12	250	6	75	20	15	17.1	1425	1.059
10	10:1	6	200	6	65	15	15	28.4	866	0.747
11	10:1	6	200	6	70	20	5	31.5	994	0.995
12	10:1	6	200	6	75	10	10	27.6	754	1.014
13	10:1	8	250	4	65	15	15	14.9	1292	1.284
14	10:1	8	250	4	70	20	5	12.3	587	1.619
15	10:1	8	250	4	75	10	10	11.1	694	1.545
16	10:1	12	150	5	65	15	15	21.5	2546	0.284
17	10:1	12	150	5	70	20	5	18.7	2412	0.369
18	10:1	12	150	5	75	10	10	19.4	2389	0.451
19	15:1	6	250	5	65	20	10	17.1	866	0.762
20	15:1	6	250	5	70	10	15	19.2	1025	0.879
21	15:1	6	250	5	75	15	5	16.5	1546	0.796
22	15:1	8	150	6	65	20	10	23.2	1864	0.354
23	15:1	8	150	6	70	10	15	35.9	1754	0.269
24	15:1	8	150	6	75	15	5	41.4	2412	0.425
25	15:1	12	200	4	65	20	10	27.5	1503	0.503
26	15:1	12	200	4	70	10	15	23.4	1875	0.354
27	15:1	12	200	4	75	15	5	31.4	1412	0.261

Subset Criteria	Number of Criteria (Variables)	Number of Position	Non-Normalized Weighted Matrix	Total (%)
SSA	1	1	1/6 × 100 = 16.67–17	17
D50	1	2	2/6 × 100 = 33.33–33	33
Grain size	1	3	3/6 × 100 = 50–50	50

S. No.	Weighted Matrix			Distance from Ideal Solution		Closeness Coefficient	Rank
	WG	WD50	WSSA	Eij+	Eij‒	CCij
1	0.11	0.10	0.01	0.12	0.05	0.31	24
2	0.15	0.12	0.01	0.16	0.02	0.09	27
3	0.12	0.09	0.01	0.12	0.05	0.30	25
4	0.09	0.06	0.02	0.08	0.10	0.55	15
5	0.08	0.06	0.02	0.07	0.11	0.59	11
6	0.08	0.06	0.02	0.07	0.10	0.58	13
7	0.06	0.05	0.04	0.04	0.13	0.75	5
8	0.07	0.05	0.04	0.05	0.12	0.73	8
9	0.07	0.05	0.04	0.04	0.13	0.74	6
10	0.11	0.03	0.03	0.08	0.11	0.59	12
11	0.12	0.03	0.04	0.08	0.10	0.55	14
12	0.11	0.03	0.04	0.07	0.12	0.63	10
13	0.05	0.05	0.05	0.03	0.15	0.84	3
14	0.06	0.02	0.07	0.01	0.16	0.91	2
15	0.04	0.02	0.06	0.00	0.17	0.97	1
16	0.08	0.09	0.01	0.10	0.09	0.47	21
17	0.07	0.08	0.02	0.09	0.10	0.53	17
18	0.08	0.08	0.02	0.09	0.10	0.53	16
19	0.07	0.03	0.03	0.04	0.14	0.76	4
20	0.07	0.04	0.04	0.05	0.13	0.73	7
21	0.06	0.05	0.03	0.05	0.12	0.70	9
22	0.09	0.07	0.01	0.08	0.09	0.53	18
23	0.14	0.06	0.01	0.12	0.07	0.36	23
24	0.16	0.08	0.02	0.14	0.04	0.23	26
25	0.11	0.05	0.02	0.09	0.09	0.52	20
26	0.09	0.07	0.01	0.08	0.09	0.52	19
27	0.12	0.05	0.01	0.10	0.09	0.46	22

S. No.	Peak Current (Ip) (A)	Pulse on Time (Ton) (µs)	Pulse off Time (Toff) (µs)	Wire Feed (m/min)	Kerf Width (mm)	MRR (mm3/min)	Ra (µm)
1	6	0.1	40	2.5	0.29	0.285	1.614
2	6	0.1	40	2.5	0.29	0.2867	1.689
3	6	0.1	40	2.5	0.29	0.285	1.594
4	6	0.2	45	3.5	0.30	0.295	1.9782
5	6	0.2	45	3.5	0.30	0.2967	1.875
6	6	0.2	45	3.5	0.30	0.3	1.8618
7	6	0.3	50	4.5	0.32	0.324	2.748
8	6	0.3	50	4.5	0.32	0.318	2.678
9	6	0.3	50	4.5	0.31	0.312	2.574
10	7	0.1	45	4.5	0.30	0.30295	2.19782
11	7	0.1	45	4.5	0.31	0.30967	2.1875
12	7	0.1	45	4.5	0.31	0.313	2.18618
13	7	0.2	50	2.5	0.32	0.319	2.8748
14	7	0.2	50	2.5	0.33	0.328	2.7678
15	7	0.2	50	2.5	0.32	0.321	2.7574
16	7	0.3	40	3.5	0.31	0.314	2.637
17	7	0.3	40	3.5	0.32	0.318	2.616
18	7	0.3	40	3.5	0.32	0.316	2.652
19	8	0.1	50	3.5	0.35	0.345	2.954
20	8	0.1	50	3.5	0.34	0.3367	2.872
21	8	0.1	50	3.5	0.34	0.341	2.836
22	8	0.2	40	4.5	0.39	0.394	3.4254
23	8	0.2	40	4.5	0.38	0.38367	3.396
24	8	0.2	40	4.5	0.40	0.399	2.439
25	8	0.3	45	2.5	0.35	0.349	3.6322
26	8	0.3	45	2.5	0.35	0.3467	3.6543
27	8	0.3	45	2.5	0.35	0.348	3.6195

S. No.	Peak Current (Ip) (A)	Pulse on Time (Ton) (µs)	Pulse off Time (Toff) (µs)	Wire Feed (m/min)	Kerf Width (mm)	MRR (mm3/min)	Ra (µm)
1	6	0.1	40	2.5	0.30	0.298	1.764
2	6	0.1	40	2.5	0.30	0.296	1.786
3	6	0.1	40	2.5	0.30	0.295	1.793
4	6	0.2	45	3.5	0.30	0.299	2.072
5	6	0.2	45	3.5	0.30	0.302	2.074
6	6	0.2	45	3.5	0.30	0.303	2.077
7	6	0.3	50	4.5	0.35	0.349	2.743
8	6	0.3	50	4.5	0.34	0.342	2.767
9	6	0.3	50	4.5	0.35	0.346	2.754
10	7	0.1	45	4.5	0.33	0.329	2.272
11	7	0.1	45	4.5	0.33	0.327	2.268
12	7	0.1	45	4.5	0.33	0.328	2.271
13	7	0.2	50	2.5	0.35	0.349	2.9574
14	7	0.2	50	2.5	0.35	0.348	2.9678
15	7	0.2	50	2.5	0.35	0.351	2.982
16	7	0.3	40	3.5	0.33	0.334	2.873
17	7	0.3	40	3.5	0.34	0.338	2.891
18	7	0.3	40	3.5	0.34	0.336	2.886
19	8	0.1	50	3.5	0.37	0.365	3.154
20	8	0.1	50	3.5	0.37	0.367	3.182
21	8	0.1	50	3.5	0.36	0.364	3.136
22	8	0.2	40	4.5	0.42	0.419	3.724
23	8	0.2	40	4.5	0.42	0.418	3.713
24	8	0.2	40	4.5	0.42	0.416	3.694
25	8	0.3	45	2.5	0.39	0.394	3.821
26	8	0.3	45	2.5	0.40	0.396	3.854
27	8	0.3	45	2.5	0.40	0.399	3.881

Subset Criteria	Number of Criteria (Variables)	Number of Position	Non-Normalized Weighted Matrix	Total (%)
Kerf width	1	1	1/6 × 100 = 16.67–17	17
Surface roughness (Ra)	1	2	2/6 × 100 = 33.33–33	33
Material removal rate (MRR)	1	3	3/6 × 100 = 50–50	50

S. No.	Weighted Matrix			Distance from Ideal Solution		Closeness Coefficient	Rank
	WK	WMRR	WRa	Eij+	Eij-	CCij
1	0.03	0.06	0.05	0.07	0.01	0.16	26
2	0.03	0.06	0.05	0.07	0.01	0.17	25
3	0.03	0.06	0.05	0.07	0.01	0.15	27
4	0.03	0.07	0.06	0.06	0.02	0.34	22
5	0.03	0.07	0.05	0.06	0.02	0.25	23
6	0.03	0.07	0.05	0.06	0.01	0.22	24
7	0.03	0.10	0.06	0.04	0.04	2.13	10
8	0.03	0.10	0.06	0.04	0.04	1.87	13
9	0.03	0.09	0.07	0.04	0.04	1.55	15
10	0.03	0.08	0.06	0.05	0.02	0.55	19
11	0.03	0.08	0.06	0.05	0.02	0.54	20
12	0.03	0.08	0.06	0.05	0.02	0.53	21
13	0.03	0.10	0.06	0.03	0.05	2.64	9
14	0.03	0.10	0.06	0.03	0.04	1.99	11
15	0.03	0.10	0.06	0.03	0.04	1.96	12
16	0.03	0.09	0.06	0.04	0.04	1.47	17
17	0.03	0.09	0.06	0.04	0.04	1.42	18
18	0.03	0.10	0.06	0.04	0.04	1.52	16
19	0.03	0.11	0.07	0.04	0.05	4.82	6
20	0.03	0.10	0.07	0.04	0.05	3.93	7
21	0.03	0.10	0.07	0.04	0.05	3.62	8
22	0.04	0.12	0.08	0.04	0.07	26.39	4
23	0.04	0.12	0.08	0.03	0.07	25.18	5
24	0.04	0.09	0.08	0.05	0.04	1.76	14
25	0.03	0.13	0.07	0.02	0.08	82.93	1
26	0.03	0.13	0.07	0.02	0.08	73.61	3
27	0.03	0.13	0.07	0.02	0.08	77.17	2

S. No.	Weighted Matrix			Distance from Ideal Solution		Closeness Coefficient	Rank
	WK	WMRR	WRa	Eij+	Eij-	CCij
1	0.03	0.06	0.05	0.07	0.04	0.36	27
2	0.03	0.06	0.05	0.07	0.04	0.36	25
3	0.03	0.06	0.05	0.07	0.04	0.36	26
4	0.03	0.07	0.05	0.06	0.04	0.38	22
5	0.03	0.07	0.05	0.06	0.04	0.38	24
6	0.03	0.07	0.05	0.06	0.04	0.38	23
7	0.03	0.09	0.06	0.04	0.04	0.52	18
8	0.03	0.09	0.06	0.04	0.04	0.52	16
9	0.03	0.09	0.06	0.04	0.04	0.52	17
10	0.03	0.08	0.05	0.05	0.03	0.39	21
11	0.03	0.08	0.05	0.05	0.03	0.39	19
12	0.03	0.08	0.05	0.05	0.03	0.39	20
13	0.03	0.10	0.06	0.03	0.05	0.59	9
14	0.03	0.10	0.06	0.03	0.05	0.59	7
15	0.03	0.10	0.06	0.03	0.05	0.59	8
16	0.03	0.10	0.06	0.04	0.05	0.57	15
17	0.03	0.10	0.06	0.03	0.05	0.57	14
18	0.03	0.10	0.06	0.03	0.05	0.57	12
19	0.03	0.10	0.07	0.04	0.05	0.57	11
20	0.03	0.11	0.07	0.04	0.05	0.58	10
21	0.03	0.10	0.07	0.04	0.05	0.57	13
22	0.04	0.12	0.08	0.04	0.06	0.62	6
23	0.04	0.12	0.08	0.04	0.06	0.63	5
24	0.04	0.12	0.08	0.04	0.06	0.63	4
25	0.04	0.13	0.08	0.03	0.07	0.67	1
26	0.04	0.13	0.08	0.03	0.07	0.67	2
27	0.04	0.13	0.08	0.03	0.07	0.67	3

S. No.	Peak Current (Ip) (A)	Pulse on Time (Ton) (µs)	Pulse off Time (Toff) (µs)	Wire Feed (m/min)	(%) Increase in Oil + Wax + Paraffin Environment vs. Deionized Water
					Kerf Width (mm)	MRR (mm3/min)	Ra (µm)
1	6	0.1	40	2.5	4.36	8.50	9.98
2	6	0.1	40	2.5	3.14	5.43	8.60
3	6	0.1	40	2.5	3.39	11.10	9.63
4	6	0.2	45	3.5	1.34	4.53	3.63
5	6	0.2	45	3.5	1.75	9.59	9.61
6	6	0.2	45	3.5	0.99	10.36	14.56
7	6	0.3	50	4.5	7.16	0.18	3.63
8	6	0.3	50	4.5	7.02	3.22	4.29
9	6	0.3	50	4.5	9.83	6.54	2.15
10	7	0.1	45	4.5	7.92	3.26	11.18
11	7	0.1	45	4.5	5.30	3.55	9.76
12	7	0.1	45	4.5	4.57	3.73	10.61
13	7	0.2	50	2.5	8.60	2.79	9.33
14	7	0.2	50	2.5	5.75	6.74	9.41
15	7	0.2	50	2.5	8.55	7.53	11.84
16	7	0.3	40	3.5	5.99	8.21	9.56
17	7	0.3	40	3.5	5.92	9.51	9.53
18	7	0.3	40	3.5	5.95	8.11	9.53
19	8	0.1	50	3.5	5.48	6.34	13.78
20	8	0.1	50	3.5	8.26	9.74	14.54
21	8	0.1	50	3.5	6.32	9.57	11.93
22	8	0.2	40	4.5	5.97	8.02	18.50
23	8	0.2	40	4.5	8.21	8.54	19.63
24	8	0.2	40	4.5	4.09	33.97	19.18
25	8	0.3	45	2.5	11.42	4.94	27.07
26	8	0.3	45	2.5	12.45	5.18	36.86
27	8	0.3	45	2.5	12.78	6.74	32.80

Residual Stress Values(MPa)	Deionized	Oil + Wax + Paraffin
	183.36	270.65

Dielectric	Roughness Factor (nm)
Deionized	143
Oil + Wax + Paraffin	249

WEDM	Deionized	Oil + Wax + Paraffin
Data Points	717	743
Rest Potential (mV)	−497.81	−512.17
LPR (Polarization Resistance)	151.39	201.45
Icorr (mA/cm2)	0.6143	0.4193
Corrosion rate mm/year	2.051	1.113
Start Potential	−250 mV
End Potential	250 mV
Sweep Rate	100 mV/min
Cycles	1
Ba (mV)	120
Bc (mV)	120

Author Contributions

G.M.V. performed all the experiments pertaining to manufacturing of the composite and machining it; S.G. supervised the complete work from funding acquisition to obtaining a grant for performing the experiment; C.S.C. assisted in characterization study and writing of manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

Department of Science Technology-Science and Engineering Research Board (DST-SERB), India (Grant No: ECR/2016/001517).

Acknowledgments

The authors acknowledge and thank the Department of Science Technology-Science and Engineering Research Board (DST-SERB), India (Grant No: ECR/2016/001517) for their financial support. The authors also extend their acknowledgement to Ram Prakash S., Junior Research Fellow.

Conflicts of Interest

The authors declare no conflict of interest.

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