# Process Optimization of Spark Plasma Sintering Parameters for Tungsten Carbide/Silicon Nitride/AA2219 Composites by Taguchi Method

Authors: Sultan Althahban; Gurusamy Pathinettampadian; Faez Qahtani; Yosef Jazaa; S. Mousa; Sanipina Anjani Devi; Melvin Victor De Poures; R. Subbiah; Hana Beyene Mamo
Journal: Advances in Materials Science and Engineering
 (2022)

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## Abstract

It is usual practice to optimize the various processing parameters in order to achieve well-organized and lucrative process conditions. For the creation of tungsten carbide/silicon nitride/AA2219 composites, sintering temperature, sintering pressure, dwelling time, and heating rate all must be optimized. Design of experiments and analysis of variance were employed to assess the factors’ contributions to density as well as microhardness response variables. It was decided to test the admixed powders and Vickers hardness tester, optical microscope, and Archimedes-based density testing to evaluate the sintered compacts. The optimum spark plasma sintering factors were a temperature of 500°C, a pressure of 30 MPa, a dwelling time of 8 minutes, and a heat rate of 160 °C/min, resulting in an extreme density of 2.71 g/cm3 and a maximum microhardness of 38.61 HV (0.38 GPa).


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## Body

## 1. Introduction

Low power consumption and quick processing times have made nonconventional spark plasma sintering (SPS) an increasingly popular sintering method [1]. MMCs and MMNCs can be fully densely consolidated at low temperatures, despite the fact that this process is still relatively new [2]. Although spark plasma sintering was first described by [3], it is now widely accepted that the rapid sintering technique was invented by them. Spark plasma sintering utilizes heat to rapidly sinter a powder compact on a macroscopic level, but it is also used at microscopic levels to deliver energy to the powder particles’ contact points [4]. When combined with plasma generation, resistive heating, and pressure application, spark plasma sintering has been proven to accomplish very rapid sintering [5]. Since the microstructure is regulated and grain development is minimal or nonexistent during the brief sintering period [6], the composite has better mechanical and thermal properties as well as chemical qualities. While other processes like SPS eliminate porosity and coarsen the microstructure of the material, spark plasma sintering minimizes the number of contaminants like H2 and O2 [7]. Numerous commercial uses have been described in the scientific literature for the usage of aluminum reinforced with a hard-secondary phase [8, 9]. In engine cylinders, rotors, commercial products, and wear application systems for all these composite materials have been shown to be effective [10].SPS of aluminium reinforced with carbon nanotubes [11] has received a large amount of attention, but the ternary tungsten carbide/silicon nitride/AA2219 nanocomposites have received little or no attention at all. When employing 500°C, 30 minutes, 30 MPa, 5 Pa vacuum and cooling rate of 500°C per minute, an SPS of [12] AA2219-tungsten carbide AA2219-tungsten carbide resulted in 300 MPa, more than three times the strength of AA2219. As a result, a number of studies are presently focused on discovering the optimum way to disperse the great features of WC on the Al matrix for use in microelectronic and electrical, energy, health, and structural applications [13]. Many writers have indicated that silicon nitride is an excellent alloying material for aluminum. A thin interdendritic flick of yielding aluminium, which sustains strains, and the occurrence of silicon nitride, which hinders crash circulation, were cited by [14, 15] as the reason for no cracking on the surface of their spark plasma sintered Al-Nb composite. Additionally, silicon nitride has been shown to exhibit exceptional fracture toughness, superb superconductivity, and great thermal and corrosion resistance in other studies [16, 17]. As a result, the properties of tungsten carbide and silicon nitride are expected to provide aluminium with higher strength, electrical and thermal conduction, and superior corrosion and wear resistance, for a wide range of engineering uses [18].MMCs have been overtaken by nanocomposites due to their superior properties, including greater toughness, lesser granular size, best wear and abrasive properties, enhanced toughness, ductileness, and exhaustion resistance [19]. In order to attain full density while conserving resources, adjusting these factors is essential. To ensure that the theoretical density of the composite is reached at minimal input factors, process parameters play an important role in experimental research [20, 21]. Al-1wt% SiC microhardness of 108 MPa and compressive strength of 312 MPa were achieved with the ideal factors of 450°C temperature, 8 minutes of dwelling time at 45 MPa pressure, and 160°C/min heat rate, according to [22, 23]. It is possible to reduce expenses and time and energy by reducing the amount of trial-and-error in experiments. Tungsten carbide/silicon nitride/AA2219 composite process parameters have received far less attention than optimization of SPS parameters [24]. Researchers in this study are utilizing ANOVA and design of experiments to refine the spark plasma sintering parameters of this composite [25]. Thus, this research makes use of spark plasma sintering process with different input parameter through Taguchi, and the corresponding mechanical properties like density and microhardness are studied for useful application.


## 2. Materials and Methods

### 2.1. Materials

The 99.5%marketable aluminum 2219 was used as the study’s starting metal. The most frequent material is used to construct liquid cryogenic rocket fuel tanks. It features one-of-a-kind mix of qualities, including outstanding cryogenic capabilities. Tungsten carbide was utilized as a reinforecement with the size of 10-30 nm. Alloy 2wt%, 2wt% WC, and 2wt% silicon nitride were combined in a dry atmosphere utilizing the Turbular Shaker Mixer model T2F for 10 hours at 110 rpm in order to ensure that the powders were thoroughly mixed. While mixing, it was required to add approximately steel balls (4 mm radius) to the vessel of powder so that the reinforcement could be better dispersed in its matrix [2].


### 2.2. Design of the Experiment

Taguchi devised a typical type of DOE known as the Taguchi technique, which is more accessible and economically viable because of the huge reduction in experimental time and expense [26, 27]. By maintaining consistency of performance and reducing variation, it is an excellent tool for optimizing process design. For the best possible responses to process variables, this powerful tool utilizes three design processes: system design, parameter design, and tolerance development [28, 29]. As a first step in the development process, system designers must identify the most critical design variables and then determine the range of acceptable values for each one. Parameter design, also known as robust design, discovers the best values for design parameters in order to reduce the effects of variance and noise [30]. Tolerance design is used to tighten tolerances in parameter design in order to acquire the best results. By employing Taguchi’s orthogonal array (OA) architecture, the manageable constraints can be evaluated with their associated answers at multiple stages in an ordered way [31]. This reduces both time and money.


### 2.3. Taguchi Method

Taguchi technique was used in this work because it is an effective tool for constructing trials when numerous variables are to be optimized, as is the situation with spark plasma sintering [32]. Because the number of tests is minimized, this method is often preferred to the factorial design method because it saves both time and money. It is thus possible to limit the number of tests by eliminating combinations of variables that are unnecessary, leaving just the most crucial combinations of parameters at their proper levels in the Taguchi’s orthogonal array experimentation method [31]. There are four factors to consider in this experiment: sintering temperature, pressure, and dwell time, as well as heating rate, all of which are shown in the table at three different levels. Respondent variables include sintered composite densities and microhardness. It was also found that the process variables were statistically significant thanks to an analysis of variance (ANOVA). Table 1 is constructed using the Taguchi L9 orthogonal array, yielding a total of nine experiments [33]. The following is the outcome: Minitab 16.1 was used to create the experiment, and the Taguchi option was used, as previously stated. Factor variables are the scientific term for the study’s four main sintering parameters. Temperature, pressure, dwell time, and heating rate were all taken into consideration. Each of the following variables was considered at three different levels: temperature (400°C), pressure (30 Mpa), dwell duration (12 minutes), and heating rate (240°C). The “factor variable” number was typed into a pop-up box, then the “level” number was entered into a pop-up box, and then ok was clicked to enable the program to begin. There are four columns in the table: temperature (A), pressure (B), dwell time (C), and heating rate(D). It was clear that steps 1 through 3 were recurrences across the data. It is possible to perform nine tests by entering varying values for three parameters: 1, 2, and 3. This yields the lowest, medium, and highest possible results.Table 1
Taguchi’s L9 arrangement.
Experimental trialsSinteringtemperatureAPressureBDwellingtimeCHeatingrateD111112122231333421235223162312731328321393321


### 2.4. Sintering Process Using a Spark Plasma

The KCE-FCT-HHPD 25 spark plasma sintering equipment was used in this work with a vacuum pressure of 0.605 bar, a relative pressure of 500 bar, and an absolute pressure of 1.2 bar. Before beginning sintering, the machine was calibrated to these settings. As needed, the admixed powder was weighed out to generate nanocomposites with a 15 mm radius and 5 mm thickness. Sintering with the settings is shown in Table2. For simpler exclusion of sintered specimen and to eliminate temperature + gradients, graphite sheets were used to hide powders from the die and the upper and lower punches [34]. A total of nine samples were gathered and analyzed, as shown in the design table.Table 2
Design of the experiment.
Experimental trialsTemperaturePressureDwelling timeHeat rate°CMPamin°C/ minA40015880B4003012160C4004516240D4501512240E450301680F450458160G5001516160H500308240I500451280


### 2.5. Testing on Density

For estimating the density of the specimen, we used the Archimedes method, whereas equation (1) was used to get the starting powder’s bulk density. Using a rule of mixes formula, the relative density of the powdered constituents was calculated using the theoretical bulk density.(1)ρbulk=%AlρAl+%WCρWC+%Si3N4ρWCSi3N4−1,where ρbulk,ρAl,ρWC, and ρSi3N4 are densities of bulk, aluminium, tungsten carbide, and siliconnitride, respectively.


### 2.6. Testing on Microhardness

Samples of the AA2219-2% WC-2% Si3N4 composites were examined on a Vicker’s microhardness tester (FM-800) using a diamond indenter with a force of 100 g for 16 seconds and a 0.1 spacing.


## 2.1. Materials

The 99.5%marketable aluminum 2219 was used as the study’s starting metal. The most frequent material is used to construct liquid cryogenic rocket fuel tanks. It features one-of-a-kind mix of qualities, including outstanding cryogenic capabilities. Tungsten carbide was utilized as a reinforecement with the size of 10-30 nm. Alloy 2wt%, 2wt% WC, and 2wt% silicon nitride were combined in a dry atmosphere utilizing the Turbular Shaker Mixer model T2F for 10 hours at 110 rpm in order to ensure that the powders were thoroughly mixed. While mixing, it was required to add approximately steel balls (4 mm radius) to the vessel of powder so that the reinforcement could be better dispersed in its matrix [2].


## 2.2. Design of the Experiment

Taguchi devised a typical type of DOE known as the Taguchi technique, which is more accessible and economically viable because of the huge reduction in experimental time and expense [26, 27]. By maintaining consistency of performance and reducing variation, it is an excellent tool for optimizing process design. For the best possible responses to process variables, this powerful tool utilizes three design processes: system design, parameter design, and tolerance development [28, 29]. As a first step in the development process, system designers must identify the most critical design variables and then determine the range of acceptable values for each one. Parameter design, also known as robust design, discovers the best values for design parameters in order to reduce the effects of variance and noise [30]. Tolerance design is used to tighten tolerances in parameter design in order to acquire the best results. By employing Taguchi’s orthogonal array (OA) architecture, the manageable constraints can be evaluated with their associated answers at multiple stages in an ordered way [31]. This reduces both time and money.


## 2.3. Taguchi Method

Taguchi technique was used in this work because it is an effective tool for constructing trials when numerous variables are to be optimized, as is the situation with spark plasma sintering [32]. Because the number of tests is minimized, this method is often preferred to the factorial design method because it saves both time and money. It is thus possible to limit the number of tests by eliminating combinations of variables that are unnecessary, leaving just the most crucial combinations of parameters at their proper levels in the Taguchi’s orthogonal array experimentation method [31]. There are four factors to consider in this experiment: sintering temperature, pressure, and dwell time, as well as heating rate, all of which are shown in the table at three different levels. Respondent variables include sintered composite densities and microhardness. It was also found that the process variables were statistically significant thanks to an analysis of variance (ANOVA). Table 1 is constructed using the Taguchi L9 orthogonal array, yielding a total of nine experiments [33]. The following is the outcome: Minitab 16.1 was used to create the experiment, and the Taguchi option was used, as previously stated. Factor variables are the scientific term for the study’s four main sintering parameters. Temperature, pressure, dwell time, and heating rate were all taken into consideration. Each of the following variables was considered at three different levels: temperature (400°C), pressure (30 Mpa), dwell duration (12 minutes), and heating rate (240°C). The “factor variable” number was typed into a pop-up box, then the “level” number was entered into a pop-up box, and then ok was clicked to enable the program to begin. There are four columns in the table: temperature (A), pressure (B), dwell time (C), and heating rate(D). It was clear that steps 1 through 3 were recurrences across the data. It is possible to perform nine tests by entering varying values for three parameters: 1, 2, and 3. This yields the lowest, medium, and highest possible results.Table 1
Taguchi’s L9 arrangement.
Experimental trialsSinteringtemperatureAPressureBDwellingtimeCHeatingrateD111112122231333421235223162312731328321393321


## 2.4. Sintering Process Using a Spark Plasma

The KCE-FCT-HHPD 25 spark plasma sintering equipment was used in this work with a vacuum pressure of 0.605 bar, a relative pressure of 500 bar, and an absolute pressure of 1.2 bar. Before beginning sintering, the machine was calibrated to these settings. As needed, the admixed powder was weighed out to generate nanocomposites with a 15 mm radius and 5 mm thickness. Sintering with the settings is shown in Table2. For simpler exclusion of sintered specimen and to eliminate temperature + gradients, graphite sheets were used to hide powders from the die and the upper and lower punches [34]. A total of nine samples were gathered and analyzed, as shown in the design table.Table 2
Design of the experiment.
Experimental trialsTemperaturePressureDwelling timeHeat rate°CMPamin°C/ minA40015880B4003012160C4004516240D4501512240E450301680F450458160G5001516160H500308240I500451280


## 2.5. Testing on Density

For estimating the density of the specimen, we used the Archimedes method, whereas equation (1) was used to get the starting powder’s bulk density. Using a rule of mixes formula, the relative density of the powdered constituents was calculated using the theoretical bulk density.(1)ρbulk=%AlρAl+%WCρWC+%Si3N4ρWCSi3N4−1,where ρbulk,ρAl,ρWC, and ρSi3N4 are densities of bulk, aluminium, tungsten carbide, and siliconnitride, respectively.


## 2.6. Testing on Microhardness

Samples of the AA2219-2% WC-2% Si3N4 composites were examined on a Vicker’s microhardness tester (FM-800) using a diamond indenter with a force of 100 g for 16 seconds and a 0.1 spacing.


## 3. Results and Discussion

In spark plasma sintering, little grain growth occurs even when the material is fully densified. Densification in these samples is attributed entirely to the complete removal of pores and grain boundaries. As seen in [35], this consolidation process is powerful enough to assure strong adhesion among the matrix and reinforcements, resulting in the high hardness and full densification of this composite. Using this technique in conjunction with the best process conditions, a composite with zero porosity and impurities can be created.Saying that spark plasma sintering is unique among fabrication methods is pointless. This is due to the tensile strength of 115 MPa obtained [36] during the induction melting of AA2219-WC.AA2219-tungsten carbide plasma spurting by [37] had a tensile strength of 83.2 MPa, which was the highest. A hardness of 38.61 HV (381.2 MPa) was achieved, which is corresponding to tensile strength of 125.4 Mpa. Sintered samples’ densities are shown in Table 3, though the ANOVA outcomes are shown in Table 4. Sintering sample density is illustrated in Figure 1 as an interplay between predictor factors. Figure 1(a) depicts the most significant graphic for relative density. The relative density amplified from 87% to 99% when the sintering temperature increased from 400 °C to 450 °C. After a further rise in temperature, the average density had reached a whopping 99.5%. In addition, a rise in pressure from 15 to 30 mega Pascal raised the comparative density from 96 to nearly 99% on the pressure plot. However, when the pressure was bigger to 45 MPa, the line began to decline by roughly 96%.Table 3
Density and microhardness testing results.
Trial no.DensityRelative densityMicrohardnessg/cm3%HV12.3989.326.9222.6196.336.4232.4389.728.4542.7297.537.6352.6598.832.1862.6999.436.5672.6897.838.6182.6898.838.5392.7199.539.04Table 4
ANOVA results on density.
Factors and interactionF valueP valueInvolvementR squared (%)SinteringtemperatureA11.660.00828.279.81PressureB0.210.832−DwellingtimeC0.140.883−HeatingrateD0.350.731−86.03AB10.150.01223.684.47AC4.870.0171289.07AD28.980.00542BC0.0140.797−BD0.0370.699−CD0.0240.732−Figure 1
Relative density main effect plot of (a) means and (b) signal to noise ratio.
(a)(b)There is a significant increase in relative density between 8 and 12 minutes and a fall between 16 and 24 minutes on the time plot. At 240°C/min, relative density peaked at 80 °C/min, and then fell back to zero, once the heat rate was improved more to 240 °C/min. This plot shows that the ideal density was achieved at 500°C, 30 MPa, 8 min of dwell time, and a heating rate of 160 °C/min. The primary effect plot of means for the signal to noise ratio in relation to density can be seen in Figure1(b). The study was done using the “bigger is better” option, and the best density was found at 500°C, 30 MPa pressure, 8 minutes dwell time, and a heating rate of 160 °C/min on the main effect plot. With [38] who sintered AA2219-tungsten carbide at 500 °C, 30 minutes, achieved an improved toughness of further than three times that of pure aluminium, which is consistent with our results (85 MPa).However, complete densification was achieved in 8 minutes rather than 15 minutes in the current investigation. Sintering temperatures over 500°C were not a possibility in this study since an SPS of AA2219-3 wt% tungsten carbide at 500 °C yielded a density of 96%, which suggests that, at 500°C, resident melting of aluminium may have begun, resulting in the drop-in density. Using the table, it can be observed that features A, AB, AC, and AD are important typical relations because they all haveP values less than 0.05. In order to achieve a fully dense tungsten carbide/silicon nitride/AA2219 composite, these are the most important characteristics to regulate. Temperature contributed 27.5% to the P value of 0.009 and had an R-squared value of 79.76% for component A. The sintering temperature, then, is all that matters for predicting the final density, with an accuracy of 79.76% when it comes to predicting the density of a sample. Assuming that temperature variance is significantly different from other parameters, the substitute suggestion that temperature has an important impact on densities can be accepted.This interaction between temperature and pressure had a R squared value of 86.3%; temperature and time had a R squared value of 0.016%; the temperature and heating rate had a R squared value of 89.7%; and temperature and pressure had a R squared value of 0.011%. One-way ANOVA models and the interactions between two components were the only models examined in this study (two-way). ANOVA results for factors related to microhardness are displayed in Table5. There is an R-squared value of 63.64% and an R-squared value of 0.048 for the temperature. Microhardness may be predicted with 63.64% accuracy by determining the sintering temperature, which considered for 15.91% of the variables that influence the microhardness. This study found that both the AC and the AD contribute significantly to the total, with AC contributing to 58.61% of the total and AD contributing to 25.63% and R-squared value of 64.81%, respectively.Table 5
ANOVA results on microhardness.
Factors and interactionF valueP valueContribution (%)R-squaredA: sintering temperature5.260.04915.9164.81B:sintering pressure0.120.908−C: dwelling time0.660.563−D: heating rate0.550.609−AB0.740.098−AC13.290.01458.61CD0.250.414−BC0.050.623−AD8.780.02225.63BD0.040.657−The rise in the microhardness of the sintered specimen may have been influenced by the variables listed above withP values less than 0.05. Temperature rises from 400 °C to 450 °C resulting in upsurge in average microhardness from 29 HV to 38 HV, according to Figure 2 which consists of ANOVA results. Temperature increases from 450 to 500°C caused in 39 HV increases. Proceeding the pressure, a rise in pressure from 15 to 45 MPa resulted in an upsurge of 35 HV to 37 HV. Microhardness decreased to 33 HV when the pressure was improved to 45 MPa (0.32 GPa). Increase in the temperature from 80 to 160 °C/min resulted in a rise from 33 (0.32 GPa) to 36 HV on the heating rate (0.35 GPa). However, increasing the rate of heating to 240 °C/min resulted in a downward trend. The time plot indicated a small rise in mean microhardness from 35 HV to 36 HV as the duration increased from 8 to 12 minutes (0.34 GPa). However, increasing the timer to 15 minutes had the opposite effect. The maximum microhardness was achieved at a temperature of 500 °C, a pressure of 30 MPa, a dwell duration of 8 minutes, and a heat rate of 160 °C/min. According to figures, a higher SN ratio is preferable, and the maximum microhardness was obtained by heating the sample to 500 °C for 8 minutes at 30 MPa pressure and heating it at 160 °C/min for a dwell duration of 8 minutes.Figure 2
Microhardness main effect plot. (a) Means. (b) Signal to noise ratio.
(a)(b)Sample densities and microhardness process parameters are plotted in Figure3. High and low density and microhardness were obtained at 500°C and 400°C, respectively. There was a clear correlation between microhardness and density at 30 MPa. The two response variables decreased as the pressure was raised more. Figure 3 shows the graph bending inward, indicating that 8 minutes of dwell time yielded the best results. The response variables decreased when the time was increased from 12 to 16 minutes. A heat rate of 160 °C/min produced the greatest results.Figure 3
Impact of processing factors on the density and microhardness of AA2219-2%WC-2% silicon nitride: (a) temperature, (b) pressure, (c) dwell time, and (d) heating rate.
(a)(b)(c)(d)


## 4. Conclusion

Spark plasma sintering has been employed to successfully create a nanocomposite of tungsten carbide, silicon nitride, and AA2219, and the following discussion is given as follows:(1)
With the incorporation of 2wt.% silicon nitride into AA2219 powder using spark plasma sintering, the microhardness was enhanced by up to 20% which is useful for a wide range of technical applications, and it was strongly influenced by factors such as temperature, dwell time, and heating rate.(2)
Density and microhardness decreased as pressure, dwelling time, and heating rate are between 30 and 45 MPa, 12 and 16 minutes, and 160 and 240 °C/min, correspondingly. According to the optimization results, the sintering parameters of 500°C temperature, 30 MPa pressure, 12 min dwell time, and 160 °C/min heating rate were found to be best for both density and microhardness.



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