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Parametric Optimization of FDM Process for Improving Mechanical Strengths Using Taguchi Method and Response Surface Method: A Comparative Investigation

Ge Gao, Fan Xu, Jiangmin Xu

2022Machines79 citationsDOIOpen Access PDF

Abstract

In the present study, a comparison of two widely used optimization approaches for fused deposition modeling (FDM), that is, Taguchi method in contrast with response surface method (RSM), was investigated. Four operating parameters, namely extrusion temperature, layer thickness, raster width, print speed, and their interaction terms, were identified as control variables with three levels, while tensile strength and compressive strength were selected responses. L27 orthogonal array and face-centered central composite design (FCCCD) were used for the experimental approach for Taguchi and RSM, respectively. The signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to find the optimal FDM parameter combination as well as the main factor that affect the performance of the PLA samples. Based on experimental results, it was observed that conclusions about significant ranking of parameters on FDM process from these two methods were different. However, both the Taguchi method and RSM succeed in predicting better results compared with the original groups. In addition, the optimum combinations for tensile strength and compressive strength obtained from the RSM were 2.11% and 8.15% higher than Taguchi method, respectively.

Topics & Concepts

Taguchi methodsResponse surface methodologyDesign of experimentsOrthogonal arrayUltimate tensile strengthFused deposition modelingMaterials scienceCompressive strengthParametric statisticsComposite materialMathematicsStatistics3D printingAdditive Manufacturing and 3D Printing TechnologiesManufacturing Process and OptimizationInjection Molding Process and Properties
Parametric Optimization of FDM Process for Improving Mechanical Strengths Using Taguchi Method and Response Surface Method: A Comparative Investigation | Litcius