1. bookVolume 28 (2022): Issue 2 (June 2022)
Journal Details
License
Format
Journal
eISSN
2353-7779
First Published
30 Mar 2018
Publication timeframe
4 times per year
Languages
English
access type Open Access

Surface Roughness Reduction in A Fused Filament Fabrication (FFF) Process using Central Composite Design Method

Published Online: 19 May 2022
Volume & Issue: Volume 28 (2022) - Issue 2 (June 2022)
Page range: 157 - 163
Received: 15 Jul 2021
Accepted: 27 Nov 2021
Journal Details
License
Format
Journal
eISSN
2353-7779
First Published
30 Mar 2018
Publication timeframe
4 times per year
Languages
English
Abstract

The objective of this study is to optimize the fabrication factors of a consumer-grade fused filament fabrication (FFF) system. The input factors were nozzle temperature, bed temperature, printing speed, and layer thickness. The optimization aims to minimize average surface roughness (Ra) indicating the surface quality of benchmarks. In this study, Ra was measured at two positions, the bottom and top surface of benchmarks. For the fabrication, the material used was the Polylactic acid (PLA) filament. A response surface method (RSM), central composite design (CCD), was utilized to carry out the optimization. The analysis of variance (ANOVA) was calculated to explore the significant factors, interactions, quadratic effect, and lack of fit, while the regression analysis was performed to determine the prediction equation of Ra. The model adequacy checking was conducted to check whether the residual assumption still held. The total number of thirty benchmarks was fabricated and measured using a surface roughness tester. For the bottom surface, the analysis results indicated that there was the main effect from only one factor, printing speed. However, for the top surface, the ANOVA signified an interaction between the printing speed and layer thickness. The optimal setting of these factors was also recommended, while the empirical models of Ra at both surface positions were also presented. Finally, an extra benchmark was fabricated to validate the empirical model.

Keywords

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