journal article·2025-11

Optimizing 3D printing parameters for enhanced compression behavior in chiral-core PLA sandwich structures

Omar Mishall Alramadan, Salman Pervaiz

Cellular Polymers· Volume 44· Issue 3-6
Publisher page

Abstract

The goal of this research is to examine how certain 3D printing parameters affect the compression behavior of Polylactic Acid (PLA) sandwich beams with a chiral core topology. The parameters examined include printing speed, infill density, and build orientation. These sandwich beams are lightweight, high-strength structures used in the construction, automotive, and aerospace industries. Their enhanced performance can also benefit the energy sector, as well as sports and medical equipment. The findings of this work will provide a framework for advancing materials science and additive manufacturing, helping to improve 3D printing procedures to achieve better mechanical properties. This research employs the Taguchi approach for experimental design to investigate how build orientation, printing speed, and infill density influence the compression behavior of PLA sandwich beams with chiral core topology. The findings revealed that build orientation of 0°, print speed of 30 mm/s and infill density of 60% provided the most optimal and superior mechanical performance as compared to all other specimens. Build orientation had the greatest influence among all parameters, contributing between 36.0% and 50.5% to the mechanical characteristics. This result aligns with previous studies, which often identify build orientation as a key factor affecting the mechanical properties of 3D-printed structures. Infill density also played an important role, contributing between 16.5% and 26.0% to strength and stiffness. Print speed’s contribution varied more widely, ranging from 2.0% to 30.8%.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Polymer Foaming and Composites · Cellular and Composite Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Rochester Institute of Technology - Dubai Campus

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