Optimisation of Process Parameters on Tensile Strength of 3D Printed Polylactic Acid (PLA) Parts: ASTM D638 Type – IV

Abstract

Purpose: The purpose of this study is to optimize the influence of 3D printing processing parameters on the ultimate tensile strength of 3D printed Polylactic Acid (PLA) parts. The objective is to develop predictive models to help predict and attain optimised mechanical strength integrity of 3D printed parts.
 Design/Methodology/Approach: In the present study, 3D printed PLA samples were modelled and fabricated using carefully selected processing parameters-processing speed, processing temperature and nozzle diameter. Tensile tests were performed by ASTM D638 standard. Two characteristics response optimisation models based on Taguchi Technique and multi-linear regression models were developed to optimise the process parameters and the ultimate tensile strength of the 3D printed samples.
 Findings: Results of this study reveal that ultimate tensile strength is significantly affected by the Nozzle diameter. The ultimate tensile strength of the 3D-printed PLA sample was found to be significantly higher than the strength of the original PLA filament printed.
 Research Implications/Limitations: In this study, only three critical 3D printing processing parameters including, processing speed; processing temperature and nozzle diameter were implemented concurrently.
 Practical implication: The optimisation of process parameters for enhancing the tensile strength of 3D-printed PLA parts holds significant practical consequences, including cost savings, improved performance, sustainability, and innovation. The aforementioned consequences render PLA a more feasible and appealing material option for a diverse array of applications and industries.
 Social implication: Optimisation of PLA printing can promote community engagement by allowing individuals to bring their creative ideas to life, fostering a sense of community and innovation.
 Originality / Value: The unique aspect of this research resides in its particular emphasis on PLA, the utilization of empirical and data-based techniques to optimise process parameters, and its potential to enhance the real-world implementation of 3D printing with PLA across diverse industries.