# Investigation into Influence of Tensile Properties When Varying Print Settings of 3D-Printed Polylactic Acid Parts: Numerical Model and Validation

## TL;DR

This study examines how different 3D printing settings affect the tensile strength of polylactic acid parts and develops a model to predict these effects.

## Contribution

A simplified mathematical model with high accuracy (R2 = 97.32%) is proposed to predict tensile properties based on print settings.

## Key findings

- The number of layers on top and bottom surfaces most strongly affects yield strength and Young’s modulus.
- Replacing layer counts with surface area fractions improves model accuracy to R2 = 97.32%.
- Experimental validation confirms the model's reliability across various print settings.

## Abstract

Material Extrusion (MEX), particularly Fused Filament Fabrication (FFF), is the most
widespread among the additive manufacturing (AM) technologies. To further its development,
understanding the influence of the various printing parameters on the manufactured parts is required.
The effects of varying the infill percentage, the number of layers of the top and bottom surfaces and
the number of layers of the side surfaces on the tensile properties of the printed parts were studied
by using a full factorial design. The tensile test results allowed a direct comparison of each of the
three parameters’ influence on the tensile properties of the parts to be conducted. Yield strength
appears to be the most affected by the number of layers of the top and bottom surfaces, which has
twice the impact of the number of layers of the side surfaces, which is already twice as impactful as
the infill percentage. Young’s modulus is the most influenced by the number of layers of the top and
bottom surfaces, then by the infill percentage and finally by the number of layers of the side surfaces.
Two mathematical models were considered in this work. The first one was a polynomial model,
which allowed the yield strength to be calculated as a function of the three parameters mentioned
previously. The coefficients of this model were obtained by performing tensile tests on nine groups of
printed samples, each with different printing parameters. Each group consisted of three samples. A
second simplified model was devised, replacing the numbers of layers on the side and top/bottom
surfaces with their fractions of the cross-section surface area of the specimen. This model provided
results with a better correlation with the experimental results. Further tests inside and outside the
parameter ranges initially chosen for the model were performed. The experimental results aligned
well with the predictions and made it possible to assess the accuracy of the model, indicating the
latter to be sufficient and reliable. The accuracy of the model was assessed through the R2 value
obtained, R2 = 92.47%. This was improved to R2 = 97.32% when discarding material infill as an
input parameter.