Research on the Effect of Technical Attributes on the Tensile Strength of FDM Products

Abstract:

Nowadays, Fused Deposition Modelling (FDM) method has been growing rapidly, which can be used to fabricate complex parts within a reasonable time. The fabrication principle of FDM method is “layer by layer” so that the previous layer and subsequent layer don’t deposit each other to create the interface between two adjacent layers. Thus, the tensile strength of FDM product along building direction depends on various process parameters. In this study, five important process parameters such as layer thickness, build orientation, build style, infill density, and print temperature are considered. The effect on tensile strength is evaluated based on the tensile test of Polylactic Acid (PLA) part. The Design of experiment (DOE) based on the Central Composite Design (CCD) to consider the relationship between the process parameters and their response through the experimental data are gathered. The suitability of model is validated by Analysis of Variance (ANOVA) and t-test. Moreover, Artificial Neural Network (ANN) is also applied to predict the response for experimental model and compared with regression equation obtained from Response surface analysis (FCCCD). The results show that the predict value of ANN model is approximate to experiment value (R² = 0.964), and the mean absolute error (MAE) of ANN model is smaller than those of FCCCD model. It is proved that ANN model is applicable to predict accurately the relationship between the process parameters and their response.

• Periodical: Key Engineering Materials (Volume 863)
• Pages: 33-50
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.863.33
• Online since: September 2020
• Authors: Huu Nghi Huynh*, Trong Hieu Bui, Thi Thu Ha Thai, Huu Tho Nguyen
• Keywords: ANOVA, Artificial Neural Networks (ANNs), Face Centered Central Composite Design (FCCCD), Fused Deposition Modelling (FDM), PLA

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