Optimising the mechanical properties of additive-manufactured recycled polylactic acid (rPLA) using single and multi-response analyses methods

Silas Z. Gebrehiwot*, Leonardo Espinosa-Leal, Paula Linderbäck, Heikki Remes

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)
65 Downloads (Pure)

Abstract

Taguchi’s design of experiment (DoE) and the grey relational analysis are used to optimise fused filament fabrication (FFF) parameters for the tensile strength and modulus of toughness (MoT) responses of a recycled polylactic acid (Reform-rPLA). The paper investigates the influences of the infill geometry, infill density, infill orientation, nozzle temperature and infill speed on the mechanical properties using the L18 orthogonal array that is based on the 2 1× 4 3 factor levels and 3 experimental repetitions. The output responses are first studied individually and combined as a multi-response optimisation using the grey relational analysis method. In the strength optimisation, the infill orientation and infill density are statistically significant with P-values α less than the 0.05 criterion. Similarly, the analysis of variance (ANOVA) for the MoT showed that infill orientation and infill geometry are statistically significant. For the multi-response optimisation, only the infill orientation is statistically significant. The mean response analyses identified factor levels that led to optimum strength and MoT responses. The confirmation tests are in good agreement with the response predictions. Using the first three influential factors, multiple variable linear regression models were developed. The predictive models showed average errors of 7.91 % for the tensile strength and 8.6 % for the MoT.

Original languageEnglish
Pages (from-to)4909-4924
Number of pages16
JournalInternational Journal of Advanced Manufacturing Technology
Volume129
Issue number11-12
Early online date11 Nov 2023
DOIs
Publication statusPublished - Dec 2023
MoE publication typeA1 Journal article-refereed

Funding

The first two authors, Silas Gebrehiwot and Leonardo Leonardo Espinosa-Leal received funding from TUF (Fonden för teknisk utbildning och forskning) via the project SUNSHINE (ID 332). The funds were used to cover salaries, material, and experimental costs.

Keywords

  • Optimisation
  • rPLA
  • Taguchi
  • Tensile Strength
  • Toughness

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