Experimental and optimization of die casting parameters on Al-Si alloy with snail shell reinforcing agent

The demand for aluminum in various fields continuously grows, including in the automotive industry. In this industry, aluminum is used as the material for the spare part. Therefore, aluminum with high mechanical properties and low casting defects is required. One of the available alternatives for producing excellent aluminum is through aluminum casting, including die casting. Die casting offers low cost in mass manufacturing of complex shaped components with acceptable casting results. Further, the selection of die-casting parameters and the addition of reinforcing elements can also improve the mechanical properties of aluminum. In this study, we strengthened the Al-Si matrix using High Pressure Die Casting process with particles from snail shell powder (calcium carbonate). Further, this study also explores the mechanical properties and microstructure of the product produced through experiment and optimization. The optimization was adopted to identify the optimum parameter. For the optimization, we used the Taguchi method. Our analysis results suggested that the reinforcing agent from the snail shell powder has the CaO and Ca(OH)2 phases, with a crystallite size of 106.59 nm. The morphology of the shell powder reinforcing agent showed the presence of agglomeration and interconnected structures, such as skeletons, with average particle size of 0.4 micro. The functional group of the shell powder reinforcing agent showed the OH band during the water absorption by CaO, along with asymmetric C–O with vibration from the carbonate group and Ca–O bound. The most excellent hardness level was identified from T8, with 86.33 HRB and die casting parameters of 0.15% reinforce agents, 750 °C temperature injection, and 50 MPa pressure. Meanwhile, the best tensile strength was found from the T9 sample, with 109,95 MPa and die casting parameters of 0.15% reinforce agents, 800 °C temperature injection, and 60 MPa pressure. Microstructure on the used piston die casting sample with snail shell powder reinforcing agent showed the presence of Al, Si, dendrite, and Al4Ca phases. The multiple response analysis on the three factors indicated that the reinforcing agent presented the most significant effects toward the tensile strength and hardness, followed by pressure and temperature injection. Meanwhile, the Taguchi method and ANOVA results showed the optimal parameter die casting was obtained from a combination of 0.15 wt% reinforce agent, 800 °C injection temperature, and 50 MPa pressure. A multiple linear regression mathematical model for tensile strength and hardness was developed from the observed data. In regression model, the value of R2 of tensile strength 74.02% and R2 of the hardness is 95,18% Thus, the developed model can be effectively used to predict the tensile strength and hardness


Introduction
The data from WBMS (World of Metal Statistics) in 2015-2017 described Indonesian positive and consistent growth of aluminum consumption.The aluminum-silicon (Al-Si) is the most popularly used aluminum alloy, primarily as a component in the automotive and aircraft industry, such as for pistons, cylinder blocks, and aircraft frames.Meanwhile, on the construction site, aluminum is commonly used as the basic material for the door and door frame.Additionally, in the food sector, aluminum is used in the construction of cooking utensils due to its high thermal conductivity supports its usage in the packaging of food and beverage [1].Besides, various uses of aluminum are due to the aluminum alloy's high wear resistance, lightweight, easy to form, better fluidity, good level of corrosion resistance, and low coefficient of thermal expansion [2].Accordingly, this high need for aluminum requires a good casting process to reduce product defects and to fulfill castings for complex and complex shapes.
Press casting (die casting) is the most precise and economical casting method, especially for the massive preparation of complex components.In the die-casting process, the liquid metal is injected into the mold cavity at high pressure.After the cavity is filled, it is cold down and compacted with rapid cooling [3].The high pressure die casting (HPDC) is one of the die-casting methods that adopts high pressure in injecting the liquid metal into the mold.This method is regarded as the most effective casting in the automotive and electronic industries as it facilitates the casting of products with complex shapes [4].In this method, the results rely heavily on the cast material, pouring temperature, pressure, and ingate velocity [4].Low pressure and temperature of liquid metal enhance the porosity rate and encourage the formation of intermetallic compounds on the casting material, which further worsens the mechanical properties of casting materials' quality.Additionally, the poring temperature also influences the fluidity and delays the freezing period, affecting the freezing of coarse particles and influencing the mechanical power of the casting [5].
The improvement of mechanical properties can be carried out by controlling the additional substances, alloying elements, degree of compaction, heat treatment, and so forth.Meanwhile, to increase the Al-Si mechanical property, researchers regulate the reinforcing material, casting process, temperature, and so forth.The reinforcement occurs from the technical as well as the mechanical reaction between the Al-Si and the reinforcing agent.This chemical reaction also occurs due to the stronger distribution in the liquid Al-Si [6].Mechanical properties can be determined by controlling the alloy microstructure.The heat treatment further defines the mechanical properties and the micro-casting.Generally, the heat treatment also produces ductility and strength of the snail shell Al-Si alloy [7].
The snail shell carries 97%-98% calcium carbonate (CaCO 3 ) [8].The available data suggested the constant increase of calcium carbonate demand, starting from the industrial era in 1983, such as in its usage as alloy material [9].The alloying with other materials increased strength, durability, toughness, and performance, leading to the emergence of studies exploring the combination of aluminum with other materials to generate new silicon aluminum (Al-Si) alloy [10].The addition of Ca on Al-Si alloy is reported to modify the needleshaped silicon into fibrous type silicon or fine silicon particles with higher strength and toughness [11].Meanwhile, the addition of CaCO 3 from seashell powder in aluminum alloy 2219 increases the hardness and friction resistance [12].Better mechanical strength of Al-Si alloy can be improved through the addition of various metals or other particles.
In this study, the Al-Si was strengthened using the particles from snail shell powder through the HPDC process.Besides, it also explores the mechanical properties and microstructure of the obtained casting produced using the experiment and optimization.For the optimization, we adopted Taguchi to identify the optimum parameter.

Experimental and optimization
2.1.Experimental work 2.1.1.Preparation of CaCO 3 powder Quail The CaCO 3 powder based on the snail shell was prepared using a synthesis process through wet ball milling facilitated by a planetary ball mill (MTI QM-3SP2) machine.In this process, water was used as a medium with a 3:1 mass fraction from the micro powder CaCO 3 sample made from snail shell.In this study, we used four different shapes of balls, three balls from each shape and the total mass of the ball is 250 gram.The sample mass (12,5 gram) was 1:20 from the total ball mass.In this study, we used 40 h of milling time with milling machine regulation every 15 min with a change of clockwise and counterclockwise rotations.The suspension from milling results was filtered using filter paper, and the obtained precipitate was dried using the oven.Then, the dried precipitate was crushed, followed by calcination for three hours at 900 °C temperature.The CaO powder was cooled down at room temperature and crushed again.The obtained CaO powder was characterized using XRD PANalytical X'Pect (λ=1,54) to identify its phase and crystallite size.For the morphology characterization, we used SEM Inspect-S50, while the functional group was characterized using FTIR DLATGS, InGaAs.

Design of die casting Al-Si experiment
The Al-Si material was obtained from the piston waste.It was characterized using XRF PANalytical Minipal 4 to identify its composition.The XRF test results are presented in table 1.
The casting method adopted in this study was the HPDC method with experiment design, as illustrated in table 2. The experiment design was from the orthogonal array L 9 (3 3 ).The used piston and snail shell powder at concentrations of (parameter A) 0.05, 0.10, and 0.15% were placed into an HPDC furnace and heated until they melted.The mixture was pressed using an HPDC piston with the pressure of (parameter B) 50, 60, and 70 MPa and a fast shot velocity of 2.5 m s −1 [15] to ensure that the liquid aluminum get into the cast.In this process, we used injection temperature variations of (parameter C) 700°C, 750°C, and 800°C, then cooled down in the air.Then the sample was processed with a lathe (Magnum Tech FEEL-1640 GCY) to prepare a tensile test specimen following the ASTM A370-16 standards, as illustrated in figure 1.The tensile test was completed using Torsee's universal testing machine (UTM) Tokyo Testing Machine MFG with a maximum weight of 50 kN.The hardness level was assessed using Torsee's Motorized Rockwell Hardness Tester type RH-3NR-A with a maximum weight of 150 kg.The microstructure of Al-Si was evaluated using a metal microscope with 650 magnification from a Nikon camera, while the macrostructure image was taken using a DSLR camera (Canon 1200D).Table 1.Chemical composition of the used as piston and standard piston. No.

Selection of process parameters
The high-pressure die-casting process involves forcing molten metal into a permanent metal mold in three phases.The first and second phases were completed with delay speed and high speed, respectively.The third stage was intensification.The high-pressure die casting contained two major phases, the fixed and moving or ejector parts.When the die casting was opened, the casting was maintained in the moving part, where it was ejected by pins either hydraulically or mechanically.The causal effect diagram was established to identify the parameters during the casting process that influence tensile strength and hardness.The reinforcement concentration (factor A), injection temperature (factor B), and pressure (factor C) were selected as the most critical parameters in the experimental design [16,17].Other parameters were maintained constantly during the experiment.The reinforcing agent was 0.05-0.15wt%, with an injection temperature of 700 °C-800 °C and a pressure of 50-60 MPa.The detail of the casting parameters is shown in table 3.

Selection of orthogonal array
Our literature review results suggested if the die-casting parameter has more than two levels, non-linear behavior from the parameter can be identified [17].Therefore, we analyzed every parameter in three levels.The obtained scores for each parameter are summarized in table 4. The total degree of freedom (DOF) for the 2 factors at each of the three levels is 6 DOF [18].After we observed the specific degree of freedom, we could analyze the orthogonal array easily.The total number of treatments was equal to the number of rows in the orthogonal column and should be equal to or greater than the degree of freedom.
Three levels of the orthogonal array with nine experiments were adopted in this study.The parameters of the casting process (A, B, and C) into the column are presented in table 2.

Results and discussion
4.1.Characterization Of CaO reinforcing agent 4.1.1.X-ray diffraction Phase identification was performed by observing the XRD characterization results to compare the crystal phase in the snail shell, as well as to analyze the grain size, crystal orientation, phase structure, and crystal defect in each phase [19].The Scherrer equation was used to measure the crystal size [20]:

Exp No
Where d is the crystal diameter, β is the Full-Width Half Maximum (FWHM), K is the constant (0.9), and λ is the wavelength (1.5406 Å).Table 5 shows the calculation results from the XRD data using the Scherrer formula.
As illustrated in figure 2, the snail shell powder obtained the highest peak at 2θ = 37,4476°, representing its CaO content.The sintering on the snail shell powder at 1100 °C temperature decomposed the CaCO 3 into CaO.This decomposition requires a minimum of 954 °C sintering temperature [21].On the other hand, the Ca(OH) 2 peaks were also observed on the snail shell powder from the reaction between the CaO and H 2 O in the air [22].Meanwhile, the Ca(OH) 2 phase originates from the water molecules absorbed on the surface of CaO, and the CaO has hygroscopic nature, enabling the absorption of water steam in the air [23].The percentage of Ca(OH) 2 content within the snail shell sample was analyzed using MATCH software.The analysis results showed 6.4% of Ca(OH) 2 .Additionally, the analysis results from the MATCH software also show the cubic crystal shape of the snail shell powder [24].

Morphology analysis
The SEM was used to observe the morphology of the samples.Figure 3 presents the morphology of snail shell powder at 25kx magnification.
The morphology on the snail shell powder shows agglomeration and interconnected structure similar to the skeleton [25,26].During the sintering process, the grains were observed to grow and shrink simultaneously, with higher temperatures and more extended sintering periods resulting in higher shrinkage.However, the effects of the period were insignificant [27].This occurrence is induced by the atom mass transport (diffusion) between particles which causes the formation of grain and pore elimination [28].Accordingly, the grain increases due to diffusion, leading to porosity among the grains.The longer sintering process lowers the porosity due to the grains moving more closely, which reduces the grain size, as well as the porosity [26].This shrinkage may also be induced by the discharge of gas during the sintering.

Molecular bonds analysis
Figure 4 and table 6 present the FTIR test results for the snail shell powder, showing the O-H band stretching at 3643,53 cm −1 peak during the water absorption by CaO [29].Meanwhile, the peaks at 1415,18 cm −1 , 1132,21 cm −1, and 875,68 cm −1 bands were correlated with the C-O asymmetric with vibration from the carbonate groups [30] .Meanwhile, the peak at 875,68 cm −1 indicates the presence of the Ca-O band [31].  5. Die-Casting Al-Si with CaO reinforcing agent

Hardness
The hardness of the samples was evaluated using Torsee's Motorized Rockwell Hardness Tester type RH-3NR-A with 150 kg maximum load.The obtained hardness of the sample is illustrated in figure 6.
As presented in figure 5, the highest hardness level was identified from sample T8, with 86.33 HRB of hardness.The addition of reinforcing elements to silicon aluminum alloys has an impact on increasing the hardness of the sample.This can be seen from the results of the hardness value in the sample without the addition of reinforcement (T0) which has a lower hardness value of 74 HRB compared to the sample with the   Ca-O addition of reinforcement.Therefore, the addition of strengthening agent on the silicon aluminium alloy at 0.05, 0.10, and 0.15% carry impacts on the sample's hardness level, as shown from the higher harness level on the samples with higher strengthening agent, from 0.05% (T1, T2, and T3), 0.10% (T4, T5, and T6), as well as 0.15% (T7, T8, dan T9).The highest hardness level was identified from the samples with 0.15% strengthening agent, in which samples T7, T8, and T9 presented hardness of 84.67 HRB, 86.33 HRB, and 85.67 HRB, respectively.A previous study from Puspitasari et al (2019) and Mardy Suhandani et al (2021) also reported that the addition of a strengthening agent improves the hardness of a material [32,33].The addition of specific elements, such as calcium, sodium, strontium, and antimony, transforms eutectic silicon into a structure with fine or finely flat fiber [34].Additionally, the Ca element in the strengthening agent facilitates the enrichment of dissolved substance in the ideal situation and improves the microstructure within the alloy optimally [35].Further, the Ca content in the aluminum alloy also modifies the Si eutectic and increases the formation of fibrous α-Al and Si eutectic dendrites [36].A previous study from Zhang et al (2019) adding Ca to the aluminum-silicon alloy also reported a higher hardness of 66.9 HB from the aluminum-silicon alloy added with 0.06% Ca, in comparison to the alloy with no Ca addition (58.6 HB) [35].
In addition, the hardness of the sample is also affected by the HPDC casting parameters, such as the injection temperature and compression [37], as shown in different hardness from T5 (750 °C) and T6 (800 °C) from different injection temperatures.The T5 has a higher hardness of 78.33 HRB than the T6 82.33 HRB.Meanwhile, excessively low injection temperature generates porosity on the casting product, leading to a lower hardness value [38].In contrast, too high injection temperature enhances the nucleus on the liquefy and purifies the microstructure of the material [39].Further, the perfected microstructure enhances the hardness of the aluminum-silicon alloy [40].
Besides, the variations of pressures during the HPDC casting process also affect the sample's hardness level, as shown in the hardness of the T1 (50 MPa) and T2 (60 MPa) samples.The T2 has a lower hardness of 76.67HRB than the T1 78 HRB.The high compression functions to push the metal liquid into the cast, but it may also trap the gas within the turbulent metal liquid flow in the die cavity [41].The trapped gas during the casting process results in gas porosity on the resulting HPDC casting product [42].

Tensile strength
A tensile test was carried out to examine the tensile strength and elongation of the sample.This test was carried out using Torsee's universal testing machine (UTM) Tokyo Testing Machine MFG, following the ASTM A370-16 standard.The samples' tensile strength and elongation are shown in figure 7.
Figure 6 shows the highest tensile strength of 109.95MPa on sample T9 and the highest elongation of 0.79% on sample T3.The addition of a strengthening agent on the silicon aluminium alloy at 0.05, 0.10, and 0.15% influences the sample's tensile strength.As shown in figure 6, the higher percentage of strengthening agent enhances the tensile strength, with the greatest tensile strength of 104.34 MPa, 108.06 MPa, and 109.95MPa observed from the samples with 0.15% strengthening agent of T7, T8, and T9, respectively.The Ca element in the strengthening agent results in the Ca-rich phase [43] and modifies the Si eutectic phase [35].A previous study from Kurnianto et al (2015) show that the adding the Ca chemical element to silicon aluminum alloy also reported an increase in tensile strength, from 99.7 MPa (without Ca) to 134.40 MPa (0.05% Ca) [44].Aside from the material's chemical compounds, the HPDC processing parameter also influences the tensile strength [45].The injection temperature selected during the HPDC casting was observed to affect the sample's tensile strength.As the 102.26MPa tensile strength of T4 (750 °C) is higher than the T6 (800 °C) tensile strength of 109.95MPa.This higher tensile strength is caused by the tagonistic effect of the temperature variation [46].At a higher temperature, the liquid metal viscosity decreases, which enhances its fluidity and reduces the porosity, then reduces the tensile strength of the casting product.The porosity of the casting products carries no effects on the yield strength, but it impacts the tensile strength and elongation of a material [37].Linearly, a previous study from Santos et al (2015) show that the applying different injection temperatures on the silicon aluminum HPDC casting reported tensile strength of 217.09MPa (579 °C), 235.71MPa (643 °C), and 244.40 MPa (709 °C) [47].Aside from the injection temperature, the compression during the casting process also influences the tensile strength of the casting product.
The variations of compression during HPDC casting also present influences on the sample's tensile strength.The tensile strength of T8 (50 MPa) is lower than that T7 (70 MPa), from 104.34 MPa to 108.06 MPa.This lower tensile strength in T8 is caused by its higher compression than T7 during the HPDC casting.The high pressure during the casting process causes turbulence, resulting in porosity which further affects the mechanical properties of the casting product [42].The porosity occurs due to the trapped gas bubbles and liquid metal shrinkage [47].The high pressure and low melting rate decrease the material's ability to evacuate the excessive gas within the cast, producing porous or hollow casting results [48].A previous study from Muhammed et al (2017) investigating the effects of different compression of 28 MPa, 39 MPa, and 49 MPa on the HPDC processing of silicon aluminum alloy also reported reduced tensile strength following the increase of pressure from 216.58 MPa (28 MPa) to 197.865 MPa [49].Therefore, the processing parameter and the addition of elements carry the mechanical features of a material [50].

Microstructure
Observation of microstructure was performed using Nikon Microscope (Japan) with camera Dino-Lite AM3111T in 996.5x enlargement.This observation goal was to find the phase distribution of Al-Si alloy.Figure 8 shows the microstructure of the samples.
As presented in figure 7, the samples' microstructure contains the primary phase of α-Al (light), the eutectic phase of Al-Si (dark) [47], and the Al 4 Ca phase [11].The observed Al 4 Ca phase in the shape of the white needle in the sample's microstructure is caused by the addition of a strengthening agent with Ca element.The presence of the Al 4 Ca phase represents the increase in strength and toughness [51].Besides, the Al 4 Ca phase within the sample also produces a smaller dendrite arm ratio [11].The dendrite in the sample is composed of a set of primary branches from (Al) and secondary branches of (Si), generating spaces between the dendrite arm, being occupied by the eutectic or intermetallic phases [52].Figure 7 also shows that samples T1, T3, and T3 have greater dendrite size than other samples, that are caused by the different HPDC casting parameters [47].The smaller dendrite size enhances the hardness of the sample [52].In samples T8 and T9, we observed a smaller size of Al distributed equally than the samples T1 and T2.Therefore, the smaller size and rounder shape of Al are induced by the optimum combination of temperature and pressure [53].

Optimization parameters die-casting 6.1. Analysis of single response
In order to obtain high efficiency in the planning and analysis of experimental data, the Taguchi design parameters were applied.The experiment data from experiments was traditionally used to analyze the mean response [54].
The (table 7) Taguchi method stresses the importance of examining the variation of the response using the signal-to-noise (S/N) ratio [55].This method was selected to minimize the variation in the quality characteristics due to uncontrollable parameters.In this analysis, the more considerable tensile strength and hardness indicate a better quality of the produced casting.The optimal setting of parameter combination is obtained by considering the highest value of the S/N ratio [56,57].For that, the S/N ratio was adopted from [58,59]: Where y i is the response value for a trial condition repeated n times.
In the next step, the S/N ratios were computed in each of the nine samples.The obtained values, the average of each parameter at different levels, and the S/N ratios of each sample are shown in tables 8 and 9.
The average samples' score from the S/N Tensile strength response ratio is presented in table 8.Meanwhile, the main effect plots presented in figure 8 suggested the highest S/N ratio for the product's tensile strength was obtained from a combination of 0.15 wt% reinforcing agent, injection temperature 800 °C, and pressure 50 MPa.Therefore, that combination of parameters is perceived as the optimum condition for obtaining the highest tensile strength.The results of ANOVA for the tensile strength are presented in table 9. On examining the percentage contributions of different factors, the percentage of reinforcing agent presents the highest contribution of about 86.25%, injection temperature has a contribution of 2.33%, pressure has a contribution of 9.61% and variables that were not studied in this study contributed 1.81%.
The average S/N response ratio is shown in table 10.Meanwhile, the main effect plots illustrated in figure 9 showed the highest S/N ratio for the material's hardness from a combination of 0.15 wt% reinforcing agent, 700 °C injection temperature, and 50 MPa pressure.That combination is the optimum condition for attaining the highest hardness level.
The results of ANOVA for the tensile strength are presented in table 11.On examining the percentage contributions of different factors, the percentage of reinforcing agent presents the highest contribution of about 90.08%, injection temperature has a contribution of 1.63%, pressure has a contribution of 7.50% and variables that were not studied in this study contributed 0.79%.

Optimal parameter combination for multi-response
For the multi-response methodology, we used Taguchi's robust design technique and utility concept for optimizing the multi-responses, like tensile strength and hardness.Taguchi's standard S/N ratios were selected to obtain the optimum parameters combination [60].
The optimum combination of casting parameters for a multi-response system on MRR and Ra was obtained from the average S/N multi-response ratio from the total utility value, as summarized in table 12 and figure 10.The higher value than the S/N multi-response ratio suggests a stronger correlation from the comparable order than the reference order.Our analysis results indicated a combination of 0.15 wt% reinforcing agent, 800 °C temperature, and 50 MPa pressure had the most excellent S/N multi-response ratio for A (reinforce agent), B (Injection temperature), and C (pressure) factors.Consequently, this combination of 0.15 wt% reinforce agent, 800 °C injection temperature, and 50 MPa pressure is the most optimum combination with the predicted S/N ratio reaching 52.0869.
The results of ANOVA for the Multi-response S/N ratios are presented in table 13.On examining the percentage contributions of different factors, the percentage of reinforcing agent presents the highest contribution of about 55.36%, and the other parameters have lower contributions.Regression analysis on tensile strength was performed at 5% significance level i.e. at 95% confidence level.R 2 is called the multiple coefficients of determination and the amount of reduction in the variability of tensile strength obtained by using the regressor variables (reinforcing agents, injection temperature and pressure).In the regression model, the R 2 value is 74.02% of the total variation explained by the model.In this case, a high R 2 value, close to 1, is desirable.From ANOVA table 14, the analysis of variance shows that terms having probability values less than 0.05 are significant.From the regression model is significant.If the residuals are plotted approximately along a straight line, then the assumption of normality is met.
An examination of the normal probability plot versus linear residuals (figure 11   unusual structure is visible.Since the standardized residuals are within the range of −3 to 3, the proposed model is significant.The residual versus order of data (figure 11(c)) shows the residual sequence of the experiment run.This implies that the residuals are random and do not show any pattern with the running order.The residual versus sequence data figure also reveals that there is no visible pattern or unusual structure in the data.This means that the proposed regression model is adequate and there is no reason to suspect any violation of the assumptions of independence or constant variation.

Regression model for hardness
Based on the Taguchi optimization results showing that the most significant parameters to the hardness value were reinforcing agents, pressure and injection temperature, a mathematical model was developed to obtain effective results.Using multiple linear regression and correlation analysis, the mathematical model for Tensile Strength is shown in equation (4).

Hardness
In the regression model of hardness, the R 2 value is 95.18% of the total variation explained by the model.In this case, a high R 2 value, close to 1, is desirable.From ANOVA table 14, the analysis of variance shows that terms having probability values less than 0.05 are significant.From the regression model at table 15, It is shown significant.If the residuals are plotted approximately along a straight line, then the assumption of normality is met.
An examination of the normal probability plot versus linear residuals (figure 12(a)) shows that the residuals lie close to the straight line implying that the errors are normally distributed and providing support that the term mentioned in the model is significant.A graph of residual values versus fitted values is shown in figure 12(b).No unusual structure is visible.Since the standardized residuals are within the range of −3 to 3, the proposed model is significant.The residual versus sequence data graph (figure 12(c)) shows the residual sequence of the experiment run.This implies that the residuals are random and do not show any pattern with the running order.The residual versus sequence data figure also reveals that there is no visible pattern or unusual structure in the data.This means that the proposed regression model is adequate and there is no reason to suspect any violation of the assumptions of independence or constant variation.

Conclusion
The results aim to investigate the optimum reinforcing agent, mechanical property, microstructure, and parameters for die casting on Al-Si Alloy with Snail Shell Reinforce Agent Using Taguchi.Therefore, several number of conclusions, including: • the XRD test results of the snail shell powder indicated the presence of CaO and Ca(OH) 2 phases, with a crystallite size of 106.59 nm; • the morphology of the snail shell powder shows agglomeration and interconnected structure similar to the skeleton with an average particle size of 0.4 micro; the functional group of the snail shell powder reinforcing agent suggested the presence of the OH band during the water absorption by CaO, along with the asymmetric C-O with vibration from the carbonate group and Ca-O band; • the best 86.33 HRB hardness was observed from the T8 sample with die casting parameters of 0.15% reinforcing agents, 750 o C temperature injection, and 50 MPa pressure; the most excellent 109.95MPa tensile strength was identified from the T9 sample with die casting parameter of 0.15% reinforcing agents, 800 o C temperature injection, and 60 MPa pressure; • the microstructure on the used piston die casting sample with snail shell powder suggested the presence of Al, Si, dendrite, and Al 4 Ca phases; the multi response analysis from the three factors shows that the reinforcing agent presents the highest effects on tensile strength and hardness, followed by the pressure and temperature injection; • based on the Taguchi method and ANOVA analysis, the optimum die casting parameter consists of 0.15 wt% reinforcing agent, 800 o C injection temperature, and 50 MPa pressure; • A multiple linear regression mathematical model for tensile strength and hardness was developed from the observed data.In regression model, the value of R 2 of tensile strength 74.02% and R 2 of the hardness is 95,18% Thus, the developed model can be effectively used to predict the tensile strength and hardness.

Figure 5 .
Figure 5. Histogram of hardness levels of HPDC Al-Si sample.

Figure 6 .
Figure 6.Tensile Strength and Elongation for HPDC Al-Si Samples with Variations of (a) Reinforcing agent, (b) Injection Temperature, and (c) Pressure.

Figure 9 .
Figure 9. Effects Plot for SN ratios on the hardness.

Figure 8 .
Figure 8. Effects plot for SN ratios on tensile strength.

Figure 10 .
Figure 10.Main effects plot based on the multi-response S/N ratio.
(a)) shows that the residuals lie close to the straight line implying that the errors are normally distributed and providing support that the term mentioned in the model is significant.A graph of residual values versus fitted values is shown in figure 11(b).No

Figure 11 .
Figure 11.(a) Normal probability plots, (b) Residuals versus the fitted values, (c) Residuals versus the order of the data of the tensile strength.

Figure 12 .
Figure 12.(a) Normal probability plots, (b) Residuals versus the fitted values, (c) Residuals versus the order of the data of the hardness.

Table 4 .
Process parameters with their ranges and values at these levels.L 9 (3 3 ) Orthogonal array.

Table 6 .
Functional groups distribution on the snail shell powder.

Table 8 .
Average values of S/N ratios at the different levels (1-3) and their effects on tensile strength.

Table 9 .
ANOVA result for S/N ratios of the tensile strength.

Table 7 .
Tensile strength, hardness values and S/N ratios against trial numbers.

Table 11 .
ANOVA result for S/N ratios of the hardness.

Table 10 .
Average values of S/N ratios at the different levels (1-3) and their effects on Hardness.Based on the Taguchi optimization results showing that the most significant parameters to the Tensile strength value were reinforcing agents, pressure and injection temperature, a mathematical model was developed to obtain effective results.Using multiple linear regression and correlation analysis, the mathematical model for Tensile Strength is shown in equation (3).

Table 13 .
ANOVA results for multi-response S/N ratio.

Table 12 .
Average values of S/N ratios at the different levels (1-3) and their effects on multi-response.

Table 14 .
Anova for regression model of tensile strength.

Table 15 .
ANOVA for regression model of hardness.