## 4 Conclusions  
In this study, two approaches are implemented to understand the effect of process parameters on mechanical properties. The first one is based on design of experiments, i.e., the central composite design of response surface methodology. A total of 31 runs were carried out. The desirability concept was used to optimize the tensile strength, impact strength, and flexural strength by obtaining the optimal settings of input process parameters, namely, infill percentage, layer height, print speed, and extrusion temperature. Secondly, the non-linear regression method was employed to predict the tensile strength, impact strength, and flexural strength. Further, the optimal input parameter settings were also obtained based on non-linear regression. The key finds are as follows:  
1. It was found that the infill percentage has a maximum effect on tensile strength and flexural strength, while extrusion temperature has a maximum effect on impact strength.
2. Mathematical models for tensile strength, impact strength, and flexural strength were developed using nonlinear regression.
3. Eventually, optimum values of tensile strength, impact strength, and flexural strength were found using the desirability approach and nonlinear regression and were validated experimentally.
4. The desirability approach predicts the tensile strength, impact strength, and flexural strength with a percentage error of less than 3.109, 6.532, and 3.712, respectively.
5. The nonlinear regression approach predicts the tensile strength, impact strength, and flexural strength with a percentage error of less than 2.977, 6.532, and 3.474, respectively.  
The future scope of this study is to work upon improvements in shear strength, fatigue strength, surface properties, and dimensional accuracy of the parts printed using PLA and, furthermore, to use a machine learning regressor and classifier for the prediction of mechanical properties, surface properties, and dimensional accuracy.  
Conceptualization, [PERSON]. ([PERSON]); methodology, [PERSON]. ([PERSON]); software, [PERSON]. ([PERSON]); validation, M.S.S.; formal analysis, M.S.S.; investigation, M.S.S.; resources, [PERSON]. ([PERSON]); data curation, N.K.K.; writing--original draft preparation, V.S.J. ([PERSON]); writing--review and editing, A.V.J.; visualization, [PERSON]. ([PERSON]); supervision, A.V.J.; project administration, N.K.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Respenses (Output Parameter)** & **Desirability Approach** & **Nonlinear Regression** & **Experimental** & **Error (\%) Desirability Approach** & **Error (\%) Nonlinear Regression** \\ \hline Tensile Strength (N/mm\({}^{2}\)) & 59.6875 & 59.6069 & 57.832 & 3.109 & 2.977 \\ Impact Strength (k/m\({}^{2}\)) & 4.3020 & 4.3020 & 4.021 & 6.532 & 6.532 \\ Flexural Strength (N/mm\({}^{2}\)) & 65.3043 & 65.1432 & 62.88 & 3.712 & 3.474 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Validation experiments.  
**Acknowledgments:** Thanks to the college administration for supporting this work. Symbiosis Institute of Technology has supported for paying the open access fee.  
**Conflicts of Interest:** The authors declare no conflict of interest.