Journal of Applied Science and Engineering

Published by Tamkang University Press

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Multi-response optimization of FDM process parameters for 3D-printed PLA+ bone screws using PCA-weighted Taguchi- based Grey Relational Analysis

 2026

 Volume 34

Sugoro Bhakti Sutono1,2, Cucuk Nur Rosyidi1, Pringgo Widyo Laksono1, and Eko Pujiyanto1

1Department of Industrial Engineering, Universitas Sebelas Maret, Surakarta, Central Java 57126, Indonesia

2Department of Industrial Engineering, Universitas Muria Kudus, Kudus, Central Java 57126, Indonesia

Received: December 27, 2025
Accepted: July 02, 2026
Publication Date: August 05, 2026

上傳圖片

Graphical representation of the mean PCA-weighted GRG for each process parameter level

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Biodegradable, patient-specific bone screw-like prototypes produced by fused deposition modeling (FDM) require careful selection of process parameters to balance mechanical integrity and manufacturing efficiency. This study optimized FDM parameters for improved PLA+ bone screw-like specimens using an integrated Taguchi-grey relational analysis (GRA) framework with principal component analysis (PCA)-derived weighting. Six parameters were investigated using an L25 orthogonal array with triplicate experiments, and the compressive strength (CS), printing time (PT), and part weight (PW) were aggregated into a weighted grey relational grade (GRG). The factor-level optimum (0.06 mm layer height, 0.6 mm wall thickness, 100% infill density, 210 ◦C nozzle temperature, 50 ◦C bed temperature, and 30 mm/s printing speed) increased the composite GRG by 3.11% relative to the best experimental trial, achieving CS ≈ 44.4 MPa with moderate PT (≈ 64.5 min) and PW (≈0.554 g). The optimized condition improved CS by 23.6% while reducing PT by 2.27% and PW by 3.99% relative to the baseline condition. Analysis of variance identified infill density as the dominant contributor
to the multi-response performance, followed by layer height and wall thickness. The results demonstrate the effectiveness of the PCA-weighted GRA for transparent multi-objective optimization in FDM. Compressive strength was used as a screening metric; further torsional, pull-out, insertion/removal torque, and fatigue tests are required for fixation-relevant qualification. The optimized parameter set is therefore presented as a local manufacturing optimum for the tested printer-filament-nozzle configuration, not as a generalized implant-design rule.

Keywords: fused deposition modeling, bone screw, multi-response optimization, Taguchi method, grey relational analysis, principal component analysis

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