Analysis of Impact Loading Response on the Composites Materials as a Function of Graphite Filler Content Using Taguchi Method

In this study, (360×10^-3) kg woven roving glass fiber with E-glass in the ((8-14) ×10^-6) m size range was employed. The matrix system used was an unsaturated polyester resin, namely the commercially available TOPAZ -1110 TP medium reactive based on Phthalic Anhydride and a room temperature hardener (Methyl Ethyl Kenton Peroxide (MEKP)). Graphite granules served as the filler (no. 7782-42-5 Merck index 10, 4410 Swiss). Injecting fillers into a polymer matrix may save production costs, increase modulus, reduce mold shrinkage, regulate viscosity, and provide a smooth surface.

All the composite honeycomb sandwich panel samples were made using the dry hand layup process described in the study [8], with a weight fraction of 30% and a graphite filler percentage of 5%, 7.5%, and 10%, respectively. Figure 1 depicts the process flow for making a composite and detailing its properties. The 54 composite honeycomb sandwich panels present with (80 mm x 40 mm x 40 mm) dimensions were manufactured.

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Figure 1. Process flow chart

Finally, a band knife cutting machine was used to form ASTM-compliant cuts in the slag and coconut shell-reinforced composite plates.

Elastic modulus, yield stress, and ultimate tensile strength are only some of the mechanical qualities that have been measured. As can be seen in Table 1, the composite's mechanical characteristics tend to improve as the filler percentage rises. Given that the filler collaborates with the fiber and resin to provide increased strength and durability. The filler and the fiber, as well as the filler and the resin, are all compatible with one another.

4.1 S/N ratio

The signal-to-noise (S/N) ratio is another fundamental component of the Taguchi technique. The S/N ratio is derived from experimental findings. Various signal-to-noise (S/N) ratios may be used to achieve the required quality level. The S/N ratio "smaller is better" has been employed in calculations since both non-destructive testing (deflection) and destructive testing (deformation) are objectives of the current study. To calculate it, use the logarithmic formula [17].

$S / N=-10 \log _{10}\left[\frac{1}{n} \sum_{i=1}^n y_i^2\right]$                   (1)

The number of observations is denoted by n, the signal-to-noise ratio by S/N, and the quantity of interest, y_i, by i. The experimental results for deflection and deformation are shown with the predicted S/N ratios for all 9 observations in Table 4.

4.2 Analysis of means

Each control parameter's influence is determined by averaging the S/N ratios at the same setting [16]. The optimal combination of the process parameters may be selected based on the findings of the mean analysis. A signal-to-noise ratio was used to construct the analysis. Table 4 summarizes the average S/N ratio values that were obtained for each parameter across all levels in response to the average impacts of deflection and deformation. For the graphite parameter impact, level-1 is the mean of the first three S/N ratio calculations shown in Table 5-a (level-1 equals an average of -14.582, -16.40495, and -16.5202). Based on the experimental layout (orthogonal array) given in Table 3, the first three rows of the L9 array correspond to the graphite parameter's level-1. Both of the other parameters and the other two levels have undergone the same process. The optimal level is the one with the maximum signal-to-noise ratio. As a result, the reaction of deflection is determined by the level combination of the three factors A2B1C1, which is comparable to (7.5% graphite), (45 g) (mass), and (90 cm) (height). Furthermore, the optimal combination level for the deformation is the same as the deflection, A2B1C1, where A2 is 7.5% graphite, B1 is 12 Kg, and C1 is 1.5 m. Table 5 shows that the parameters' relative importance varies depending on the kind of analysis being performed, with the mass parameter being more important for calculating bending moments than any of the others, while the graphite parameter is more important for calculating bending moments. This is determined by the parameter rank, which is the maximum minus minimum value of the three levels for each parameter.

Table 4. Nondestructive test and destructive test

Table 5. Mean S/N ratio for each factor level of

The underlined value represents the optimum level (A2B1C1)

Using the information supplied in Table 5, the primary impact of the S/N ratio is shown visually in Figure 3. For both destructive and non-destructive testing, the figures depict the correlation between the S/N ratio and parameter values. Graph 2 shows that the S/N values consistently decrease as the mass increases. As a result, the smaller mass will result in the smallest bending moment. The graph also reveals that the greatest mean S/N value is found at graphite level 2. In the case of mass, the largest S/N mean is found at level 1. Levels 1 and 2 seem to have the same impact and are closer to a straight-line connection when the height parameter is included. This indicates that the deflection is not significantly affected by whether using level -1 or level -2. However, Figure 3 demonstrates that the mass and height parameters are related to deformation, suggesting that these two factors share the same impact. To rephrase, more deformation occurs as height or mass increases. In addition, the best level is the one that produces the greatest S/N ratio on the graph. Therefore, the parameters and their values of A2B1C1 are the best possible combination.

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Figure 3. Representation of S/N ratio versus levels of each parameter for the destructive test

4.3 Analysis of variance (ANOVA)

Table 6. ANOVA

The purpose of the ANOVA statistical approach is to investigate the effect of various design elements on the overall variation of the outcomes [18]. Deflection and distortion ANOVA findings are shown in Table 6. Mass, as can be shown in Table 6-a, is the most important factor, accounting for 44.48% of the total variation in the process. Therefore, it is the most important factor in determining deflection (by 35.95%). Height has less of an impact than width and depth. It is also evident from the relative contributions of the three factors that the mass parameter is the most important one, followed by the graphite% and the height parameter. Table 6–b reveals that the graphite parameter contributes 82.39% to the deformation, making it the most important one. The height parameter comes in second, followed by the mass. The findings of the analysis of variance and the results of the analysis of mean are identical.

4.4 Confirmation test

Confirmation tests are performed as the last stage of experimental design. Predicting and verifying inference derived during the analysis state and improvements in observed values by using the optimum level of process parameters [17, 19, 20] are the goals of this exercise. The optimal values of deflection and deformation are used in the confirmation experiment. Consequently, the formula for the deflection is graphite (7.5%, 45 g, 90 cm) while the formula for the deformation is graphite (7.5%, 12 Kg, 1.5 m). This equation [17] may be used to determine the ideal S/N ratio for a given set of process parameters.

$\eta_{o p t}=\eta_m+\sum_{i=1}^k\left(\eta_i-\eta_m\right)$                    (2)

where:

η_opt: predicted S⁄N ratio.

η_m: Total mean of S⁄N ratios.

η_i: mean S⁄N ratio at optimum levels.

k: number of main design parameters that affect the quality characteristics.

In order to compare the anticipated S/N ratio with the observed value, an experiment was performed using the combination A2B1C1, for both, deflection and deformation. Based on the variables listed in the last column of Table 4, a deflection value of (_m=-15.69401 dB) for the overall mean S/N ratio were obtained. the value for distortion of (_m=-19.53263 dB). The cumulative mean of the S/N ratio have been utilized in conjunction with the highlighted variables in Table 5 to get the optimal anticipated value of S/N. The confirmation test findings are summarized in Table 7.

Table 7. Confirmation results