Optimizing additive manufacturing parameters for graphene-reinforced PETG impeller production: A fuzzy AHP-TOPSIS approach
Additive manufacturing, particularly 3D printing, has transformed production by enabling precise, layer-by-layer construction with minimal material waste. This study aims to optimize the mechanical properties and production efficiency of impellers manufactured using Graphene-Reinforced Polyethylene...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024012738 |
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| Summary: | Additive manufacturing, particularly 3D printing, has transformed production by enabling precise, layer-by-layer construction with minimal material waste. This study aims to optimize the mechanical properties and production efficiency of impellers manufactured using Graphene-Reinforced Polyethylene Terephthalate Glycol (G-PETG) filament. By employing the Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), we identified optimal 3D printing parameters. The results showed that a 65 % infill density, 0.20 mm layer height, 50 mm/s printing speed, 90 °C platform temperature, 240 °C extruder temperature, and 90 mm/s traverse speed led to a 15 % improvement in tensile strength and a 12 % reduction in production time compared to baseline settings. Additionally, the impellers produced demonstrated superior surface finish and structural integrity, making them suitable for high-performance applications. These findings underscore the importance of parameter optimization in enhancing the performance of 3D-printed components, particularly for applications requiring high mechanical strength and precision. |
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| ISSN: | 2590-1230 |