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Corresponding Author

Rania Ben Amor

Authors ORCID

Rania Ben Amor: https://orcid.org/0000-0002-4424-9364

Document Type

Article

Keywords

FDM, PLA, PETG, Dimensional error, Grey relational analysis, Multi-objective optimization, Taguchi method, Dimensional accuracy

Abstract

This study investigates the multi-level Grey Relational Analysis (GRA) for the simultaneous optimization of dimensional accuracy and productivity in Fused Deposition Modeling (FDM) of PLA and PETG spur gears. A Taguchi L9 orthogonal array was employed to evaluate the influence of key process parameters, including layer thickness, printing speed, and flow rate. Dimensional accuracy was assessed through multiple geometrical responses, namely internal diameter (Di), head diameter (Da), tooth thickness, and base thickness (Sb). These responses were integrated into a single performance index using Grey Relational Analysis. The results show that the optimal condition for PLA (Exp 9) achieves a maximum GRG of 0.856 and simultaneously minimizes printing time (54 min), indicating a Pareto-optimal solution. In contrast, PETG exhibits a trade-off behavior, where the optimal configuration depends on the selected objective (quality vs productivity). ANOVA results reveal that layer thickness is the most influential parameter, contributing up to 55% to dimensional accuracy and 75% to printing time. The proposed multi-level optimization framework provides a robust decision-making tool for improving both geometric precision and manufacturing efficiency in FDM-printed functional components.

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