Application of Taguchi method to optimize ultrasonic vibration assisted fused deposition modeling process parameters for surface roughness
This paper presents the findings on the process parameters for surface roughness optimization of an open-source ultrasonic vibration assisted fused deposition modeling (FDM) printed specimen. Acrylonitrile Butadiene Styrene (ABS) material for the specimens and the printing temperature, layer thickn...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit UTM
2022
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28249/2/0075215072024103520.pdf http://eprints.utem.edu.my/id/eprint/28249/ https://journals.utm.my/jurnalteknologi/article/view/18431 https://doi.org/10.11113/jurnalteknologi.v84.18431 |
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| Summary: | This paper presents the findings on the process parameters for surface roughness optimization of an open-source ultrasonic vibration assisted fused deposition modeling
(FDM) printed specimen. Acrylonitrile Butadiene Styrene (ABS) material for the specimens and the printing temperature, layer thickness, and surface layer were determined as the control parameters that influenced the surface roughness. Experimental design with Taguchi level 9 (3*3) Orthogonal Arrays (OA) was designed with nine experimental runs. Three levels of each control factor was identified. In addition, data for multi-responses of build time and surface roughness was obtained by utilizing and conducting the nine-requirement experimental run for Taguchi Method. The specimens were printed using an
open-source ultrasonic vibration assisted FDM printer with a 20kHz ultrasonic vibration supplied to the printing platform of the printer. Analysis of variance (ANOVA) was conducted to determine whether p-values are significant with the model or otherwise. The experiments examined the build time and surface roughness, the responses were collected and optimized by using the grey relational grade (GRG). The result shows no correlation between build time and surface roughness in the grey relational grade, and the p-value was higher than 0.05 significant level. However, the surface roughness for optimal level combination setting showed the obvious result, which the settings consist of printing temperature (level 1), layer thickness (level 1), and surface layer (level 1). |
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