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IJMERR 2022 Vol.11(7): 527-534

Strength Optimization and Strength Prediction of Fused Deposition Modelled Specimens Based on Process Parameters

Maurice P. Schwicker 1, Nikolay D. Nikolov 2, and Marco Häßel 1
1. University of Applied Sciences – Kaiserslautern, Department of Applied Engineering Sciences, Kaiserslautern, Germany
2. Technical University of Sofia, Department of Mechanics, Sofia, Bulgaria

Abstract—There are many factors, which influence the strength of parts produced by Fused Deposition Modeling. In this study, the effects of main manufacturing process parameters are quantified and optimized using the Design of Experiment approach, in order to produce components with higher tensile strength. First, the main manufacturing parameters, which can be set in the slicing software, are explained. Ten parameters are selected for strength optimization, using standard tensile test specimens. The strength and elasticity modulus resulting from the parameters sets are determined and evaluated. It was found that the nozzle diameter, top and bottom layer orientation, infill amount and layer height have a major influence on strength. Additionally, the effects of filament color and time after building are examined and their effect on strength was found to be negligible. A regression model is developed to calculate optimized parameter sets. The model was verified, resulting in a 7% higher tensile strength than the strongest specimen in the experiment design. Using the same model, an equation for prediction of tensile strength is proposed.

Index Terms—fused deposition modelling, strength optimization, strength prediction, design of experiment, process parameters

Cite: Maurice P. Schwicker, Nikolay D. Nikolov, and Marco Häßel, "Strength Optimization and Strength Prediction of Fused Deposition Modelled Specimens Based on Process Parameters," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 7, pp. 527-534, July 2022. DOI: 10.18178/ijmerr.11.7.527-534

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.