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December 5, 2025Sustainability3 citationsOpen Access

Multi-Objective Optimization of Fatigue Performance in FDM-Printed PLA Biopolymer Using Grey Relational Method

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KAKarla AntunovićPLPetar Ljumović

Key Points

  • Fatigue performance improved through optimized process parameters, contributing to mechanical reliability.
  • Results indicate the use of the Grey Relational Method in optimization, yielding a balance of efficiency.
  • Key process parameters include layer height, infill density, and perimeters affecting fatigue strength and printing time.
  • Supports greater adoption of sustainable materials in additive manufacturing by enhancing PLA performance.

Abstract

This study focuses on improving the fatigue strength and overall performance of sustainable biopolymer polylactic acid (PLA) components manufactured via Fused Deposition Modelling (FDM) additive manufacturing process. PLA, as a biodegradable and renewable polymer derived from natural resources, represents a promising alternative to conventional petroleum-based plastics in engineering and research applications. The influence of key FDM process parameters—layer height, infill density, and number of perimeters—on critical performance indicators such as filament consumption, printing time, and fatigue strength (number of cycles to failure) was systematically analyzed using the Taguchi L9 orthogonal array. Subsequently, Grey Relational Analysis (GRA) was applied as a multi-objective optimization technique to identify the parameter settings that achieve an optimal balance between mechanical durability and resource efficiency. The obtained results demonstrate that a proper combination of process parameters can significantly enhance the mechanical reliability and sustainability profile of FDM-printed PLA parts, contributing to the broader adoption of eco-friendly materials in additive manufacturing.

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Cite This Study

Antunović et al. (2025) studied this question.

synapsesocial.com/papers/6940224e2d562116f28fc0b0https://doi.org/10.3390/su172410902
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