## 4 Discussion and Findings
Furthermore, the optimal A, B and C parameter values were determined for all responses using the desirability function \"d\" as well [23; 24; 25; 26], which is also used to analyze several responses, assess their quality and pick out the best alternative with the greatest characteristics; the desired response peak levels (di) must be reflected. It is therefore possible to use the calibrated responses on a purely qualitative scale of desirability. It is possible to have an unwelcome response (d = 0) and a desired one at the same time (d = 1). When  
Figure 3: At a temperature of 274.23 degrees Celsius, feed rate and speed are processed together. \begin{table}
\begin{tabular}{c c} \hline \hline
**Estimate Response** & **The Model of Regression** \\ \hline Light–dark (dL*) & \(+12.35-0.0117\times\mathrm{T}-0.0188\times\mathrm{S}-0.220\times\mathrm{FR}+3. 10\times 10^{-4}\times\mathrm{S}\times\mathrm{FR}+08.39\times 10^{-6}\times\mathrm{S }^{2}\) \\ \hline Green–red (da*) & \(-34.34+0.2050\times\mathrm{T}+0.024\times\mathrm{S}+0.070\times\mathrm{FR}-2.160 7\times 10^{-4}\times\mathrm{T}\times\mathrm{FR}+1.208\times 10^{-4}\times \mathrm{S}\times\mathrm{FR}-4.0780\times 10^{-4}\times\mathrm{T}^{2}\) \\ \hline Yellow–blue (db*) & \(-19.240+0.180\times\mathrm{T}-5.0020\times 10^{-4}\times\mathrm{S}-0.0779\times \mathrm{FR}+2.50\times 10^{-4}\times\mathrm{S}\times\mathrm{FR}-3.660\times 10^{-4}\times \mathrm{T}^{2}-2.860\times 10^{-3}\times\mathrm{FR}^{2}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Regression model’s simulation data. all of the criteria are optimally integrated, the value is at its highest level. There are three aspects to the narrative. At a feed rate of 24.44 kg/h, 274.23 \({}^{\circ}\)C and a speed of 728.38 rpm, the greatest combined desirability was determined to be 87%, as shown in Figure 4.  
In Figure 5, an overlay plot of process outlines with speed vs. temperature is shown, which highlights the potential zone for reaching the intended values. The dL*, da* and db* measured responses have been attained with the FR maintained constant when FR = 24.44 kg/h; yellow represents the portion of the graph that lies within 0.30 da* and 0.20 db*. The settings of FR of 24.44 kg/h, T of 274.23 \({}^{\circ}\)C and speed of 728.38 rpm make it possible to achieve the best possible tri-stimulus values: da* equals 0.19, dL* equals \(-\)0.01 and db* equals \(-\)0.188. Equation 1 yields a tri-stimulus variance value of no more than 0.26. When viewed within the context of the allowed maximum variance, this is a respectable figure, dE* equals 1.0, according to the research findings. The experimental design utilized process variables; full factorial RSM was used, with three stages of process variables and a variety of processing conditions (GT). RSM and GT were statistically significant in producing process parameters [27; 28; 29; 30; 31]. Indeed, the present study demonstrates, from the output of the appropriate color, a little deviation is revealed by an optimized set of temperature, feed rate and screw speed values in the context of the processing parameters' specified range. In addition, more research can be performed to determine the optimal processing conditions for various color formulations and grades, leading to a significant reduction in waste [27; 28; 29; 30; 31; 32]. As a result, a total variance (dE*) of 0.26 means that the enhanced tri-stimulus values of BBD in this investigation are suitable for the desired values. Using GT allowed determining the lowest color output variation to be at 255 \({}^{\circ}\)C, 25 kg/h and 750 rpm (the mid-point between these three parameters). Figure 4: Desirability diagram for a feed rate of 24.4 kg/h. Table 6 shows that dE* = 0.35 within such a specified range of process variables is noticed. In the GT design, a total of 15 processing parameters were tested to optimize the best or optimum color output. Interestingly, the optimal color was found at the center point of the experimental setup.