3.8 Article

Experimental investigations on effect of graphite loading on melt flow behaviour of ABS-Gr composite for fused filament fabrication (FFF) process

Journal

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/2374068X.2022.2093004

Keywords

Additive manufacturing; ABS pellets; graphite; FFF; ANOVA; melt flow index (MFI); design of experiments (DOE); melt flow rate (MFR)

Ask authors/readers for more resources

This study investigates the melt flow rate (MFR) of ABS composite by varying the proportion of graphite (Gr) powder and examines its suitability for FFF process. The results show that extrusion temperature is the most influential parameter and the error in the experimental study is minimal. The optimal process parameters combination is determined through a signal-to-noise (S/N) ratio analysis.
In FFF process, the melt flow rate (MFR) of the polymer matrix composite material is an important factor in selecting the appropriate process parameters for printing parts. Concerning FFF, MFR and the extrusion temperature (ET) are important parameters due to their influence on the degree of layer adhesion and strength. The current study aims to investigate the MFR of ABS composite by varying the proportion of graphite (Gr) powder. The effects of Gr loading (5, 10, and 20 wt%) on MFR of composite and suitability for FFF process were investigated using MFI machine under different extrusion temperatures and extrusion loads. ANOVA and S/N ratio analysis were used to determine the significance of each process parameter and percentage of error involved in experiments. The experiments were performed three times at set of levels to find optimum response and reduces the error. The results shows that ETmost influential parameter among others, error was less than 1% in the experimental study. A signal-to-noise (S/N) ratio analysis is performed to optimise process parameters, with 'larger is the better' criterion. The combination ET3-EL3-FL1 i.e. ET 240 degrees C, EL 5 kg and FL 5 wt% is observed as optimal process parameters values to get optimal MFR.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

3.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available