{"id":9677,"date":"2026-08-05T21:51:27","date_gmt":"2026-08-05T13:51:27","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=9677"},"modified":"2026-08-06T22:58:34","modified_gmt":"2026-08-06T14:58:34","slug":"jase-202611-34-007","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202611-34-007","title":{"rendered":"Multi-response optimization of FDM process parameters for 3D-printed PLA+ bone screws using PCA-weighted Taguchi- based Grey Relational Analysis"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 34<\/a><\/p>\n<\/div>\n\n\n\n

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Sugoro Bhakti Sutono1,2<\/sup>, Cucuk Nur Rosyidi1<\/sup><\/i><\/a>, Pringgo Widyo Laksono1<\/sup>, and Eko Pujiyanto1<\/sup><\/p>\n\n\n\n

1<\/sup>Department of Industrial Engineering, Universitas Sebelas Maret, Surakarta, Central Java 57126, Indonesia<\/p>\n\n\n\n

2<\/sup>Department of Industrial Engineering, Universitas Muria Kudus, Kudus, Central Java 57126, Indonesia<\/p>\n<\/div>\n\n\n\n

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Received: December 27, 2025
Accepted: July 02, 2026
Publication Date: August 05, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Graphical representation of the mean PCA-weighted GRG for each process parameter level<\/p>\n<\/div>\n<\/div>\n\n\n\n

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

Download Citation:\u00a0 BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202611_34.007<\/a>\u00a0\u00a0<\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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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<\/sub>), printing time (PT<\/sub>), and part weight (PW<\/sub>) 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 \u25e6<\/sup>C nozzle temperature, 50 \u25e6<\/sup>C bed temperature, and 30 mm\/s printing speed) increased the composite GRG by 3.11% relative to the best experimental trial, achieving CS \u2248 44.4 MPa with moderate PT (\u2248 64.5 min) and PW (\u22480.554 g). The optimized condition improved CS by 23.6% while reducing PT<\/sub> by 2.27% and PW<\/sub> 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.<\/p>\n\n\n\n

Keywords: fused deposition modeling, bone screw, multi-response optimization, Taguchi method, grey relational analysis, principal component analysis<\/em><\/p>\n\n\n\n

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