Effect of Sterilization on the Dimensional and Mechanical Behavior of Polylactic Acid Pieces Produced by Fused Deposition Modeling

Abstract

To successfully implement additive manufacturing (AM) techniques for custom medical device (MD) production with low-cost resources, it is imperative to understand the effect of common and affordable sterilization processes, such as formaldehyde or steam sterilization, on pieces manufactured by AM. In this way, the performance of low-risk MDs, such as biomodels and surgical guides, could be assessed for complying with safety, precision, and MD delivery requirements. In this context, the aim of the present work was to evaluate the effect of formaldehyde and steam sterilization on the dimensional and mechanical stability of standard polylactic acid (PLA) test pieces produced by fused deposition modeling (FDM). To achieve this, PLA samples were sterilized according to the sterilization protocol of a public hospital in the city of Bucaramanga, Colombia. Significant changes regarding mechanical and dimensional properties were found as a function of manufacturing parameters. This research attempts to contribute to the development of affordable approaches for the fabrication of functional and customized medical devices through AM technologies, an issue of particular interest for low- and middle-income countries.

Keywords: additive manufacturing; material extrusion (MEX); polylactic acid (PLA); sterilization.

Figure 1

Machine coordinate system. Source: image based on ASTM [53].

Figure 2

The geometry of type IV specimen. (Lc) Nominal rated length, 25 mm. (Lt) Total nominal length, 115 mm. (W) Nominal minor width, 6 mm. (Wo) Nominal width, 19 mm. (e) Nominal thickness, 4 mm. Source: based on ASTM [53].

Figure 3

PLA samples: (a) building procedure, (b) tensile test setup.

Figure 4

Stress–strain curves for 30% infill samples.

Figure 5

Stress–strain curves for 60% infill samples.

Figure 6

Stress–strain curves for 90% infill samples.

Figure 7

Data distribution for all sample groups that were evaluated. Min (Minimum), Q1 (1st Quartile), Q3 (3rd Quartile), Max (Maximum), δ (Standard deviation), E (Young’s modulus), Sy (Yield Strength), Su (Ultimate strength).

Figure 8

Hierarchical clustering: (a) gap statistic between 0 to 1 for k clusters up to 10. (b) dendrogram for k = 8 clusters and samples’ number corresponding with Table 3. Dash line indicated the cluster analysis for determine a suitable k value.

Figure 9

Principal components reduction (PCA) from hierarchical clustering k = 6 clusters. Colors 1 to 6 correspond to each cluster. Euclidian distance. Linkage method Ward.D. Numerical data from 1 to 18 represent each sample.