**3. Results and Discussion**

For improving the quality of the experiments and reducing the tests, the DOE approach was utilized. This method could be a link between input and output parameters with a logical and physical condition resulting from the primary experiment. For each of 20 samples in the first level of the experiment, the maximum failure load, thickness, and build time were measured. Design Expert V08 software, based on the regression equations and ANOVA table, sorted parameters for each output. In this stage of the experimental study, the results of the output parameters were analyzed. This composite was more flexible than the 3D printed PLA materials, but the failure load in the Br-PLA was less than PLA.

## *3.1. Maximum Failure Load*

The ANOVA table showed that the layer thickness was the dominant controlled variable for the maximum failure load. Extruder temperature and infill percentage were also significant. Table 4 demonstrates the ANOVA results of the maximum failure load.


**Table 4.** Analysis of variance (ANOVA).

Equation (1) is a predictive model of maximum failure load in terms of coded factors. Also, Equation (2) shows a predictive model of maximum failure load with respect to the actual values.

$$\begin{aligned} \text{(Maximum Fahure Load)}^{2.32} &= 9250115 + 473024.5 \text{ LT} - 538606 \text{ IP} + 434805.5 \text{ ET} \\ + 4398413 \text{ LT} \times \text{IP} + 3926069 \text{ LT} \times \text{ET} - 3412710 \text{ LT}^2 - 3693896 \text{ ET}^2 \end{aligned} \tag{1}$$

$$\begin{aligned} \text{(Maximum Failure Load)} \, ^{2.32} &= -1.4 \times 10^8 - 1.2 \times 10^8 \,\text{LT} - 411791 \,\text{IP} + 1591377 \,\text{ET} \\ + 1099603 \,\text{LT} \times \text{IP} + 654344.9 \,\text{LT} \times \text{ET} - 8.5 \times 10^7 \,\text{LT}^2 - 4104.33 \,\text{ET}^2 \end{aligned} \tag{2}$$

The developed equation was useful to determine the relative significance of factors by comparing the factor coefficients. Also, Figure 5 shows the perturbation plot of the maximum failure load. The perturbation plot helped to compare the effect of all factors in the central point in the design space, as illustrated in Figure 5. The maximum failure load was plotted by changing only a factor over its range, while other factors were kept constant. Lines A, B, and C showed the sensitivity of maximum failure load to layer thickness, infill percentage, and extruder temperature, respectively. The perturbation plot disclosed increasing layer thickness and extruder temperature parameters that resulted in an increase in the mechanical strength of specimens. In addition, the plot showed that the maximum failure load depended almost equally on the extruder temperature. Figure 6a demonstrates the effects of the layer thickness and infill percentage on the maximum failure load. The IP had a very specific role in flexibility and tensile strength because by increasing the IP, the structure of 3D parts went to denser structure with lower porosity. Therefore, samples printed by high IP could resist the great tensile load, even though these samples did not have good flexibility properties. A 3D surface plot of maximum failure load with respect to the layer thickness and extruder temperature is shown in Figure 6b. It is clear that thinner samples under dramatic forces could not resist much. Figure 7 indicates the normal probability plot of the residuals to check for normality of residuals. The normal probability plot indicated whether residuals followed a normal distribution; in this case, the points followed a straight line. Some moderate scattering was also expected even with normal data.

**Figure 5.** Perturbation plot of the maximum failure load.

**Figure 6.** *Cont.*

**Figure 6.** 3D surface plot of the maximum failure load with (**a**) infill percentage and layer thickness; (**b**) extruder temperature and layer thickness; (**c**) infill percentage and extruder temperature.

**Figure 7.** The normal plot of residuals of the maximum failure load.
