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February 16, 2026Applied Sciences4 citationsOpen Access

Multi-Objective Optimization of PLA Biopolymer FDM 3D Printing for Improved Impact Strength, Surface Quality and Production Efficiency via Grey Relational Analysis

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KAKarla AntunovićIPIvan PekoNČNikša Čatipović

Key Points

  • The research aims to optimize parameters for FDM 3D printing of PLA to enhance impact strength, surface quality, and production efficiency.
  • Examined layer height, infill density, and number of perimeters in FDM printing.
  • Utilized a Taguchi L9 orthogonal array for experimental design and analysis.
  • Applied regression-based models to quantify effects of parameters on impact strength and surface quality.
  • Employed Grey Relational Analysis for multi-objective optimization.
  • Achieved a balance between impact strength and production efficiency through optimal parameter settings.
  • Established correlation between surface roughness and process parameters.
  • Provided parameter combinations that enhance both mechanical durability and surface quality while minimizing resource use.

Abstract

This study investigates the influence of layer height, infill density, and the number of perimeters on the FDM 3D printing performance of PLA, a biodegradable and renewable biopolymer. The primary objective is to identify parameter settings that simultaneously maximize impact strength and production efficiency, quantified through filament usage and printing time. In addition, 3D surface profilometry was employed as a non-destructive characterization method to evaluate surface roughness, assess its dependence on process parameters, and establish correlations with destructive impact strength testing. Experimental work was conducted using a Taguchi L9 orthogonal array, and regression-based mathematical models were developed to quantify the effects of individual parameters on the analysed responses. Finally, Grey Relational Analysis (GRA) was applied to perform multi-objective optimization and determine parameter combinations that jointly enhance mechanical durability, surface quality, and production efficiency. The results provide a clear set of manufacturing parameter settings that satisfy both destructive and non-destructive performance criteria while ensuring resource-efficient production.

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Cite This Study

Antunović et al. (2026) studied this question.

synapsesocial.com/papers/6992b5649b75e639e9b09e12https://doi.org/10.3390/app16041871
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