Experimental analysis and optimization of mechanical properties of FDM-processed polylactic acid using Taguchi design of experiment - Université Savoie Mont Blanc Access content directly
Journal Articles International Journal for Simulation and Multidisciplinary Design Optimization Year : 2021

Experimental analysis and optimization of mechanical properties of FDM-processed polylactic acid using Taguchi design of experiment

Mohamed Abouelmajd
Ahmed Bahlaoui
  • Function : Author
Ismail Arroub
Maria Zemzami
  • Function : Author
Nabil Hmina
  • Function : Author
Soufiane Belhouideg

Abstract

Fused deposition modeling (FDM) is one of the most used additive manufacturing processes in the current time. Predicting the impact of different 3D printing parameters on the quality of printed parts is one of the critical challenges facing researchers. The present paper aims to examine the effect of three FDM process parameters, namely deposition velocity, extrusion temperature, and raster orientation on the bending strength, stiffness, and deflection at break of polylactic acid (PLA) parts using Taguchi design of experiment technique. The results indicate that the temperature has the highest impact on the mechanical properties of PLA specimens followed by the velocity and the orientation. The optimum composition offering the best mechanical behavior was determined. The optimal predicted response was 159.78 N, 39.92 N/mm, and 12.55 mm for the bending strength, bending stiffness, and deflection at break, respectively. The R 2 obtained from analysis of variance (ANOVA) showed good agreement between the experimental results and those predicted using a regression model.

Dates and versions

hal-04161171 , version 1 (13-07-2023)

Identifiers

Cite

Mohamed Abouelmajd, Ahmed Bahlaoui, Ismail Arroub, Maria Zemzami, Nabil Hmina, et al.. Experimental analysis and optimization of mechanical properties of FDM-processed polylactic acid using Taguchi design of experiment. International Journal for Simulation and Multidisciplinary Design Optimization, 2021, 12, pp.30. ⟨10.1051/smdo/2021031⟩. ⟨hal-04161171⟩

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