| Autor: |
Tsiolikas, Aristeidis, Kechagias, John D., Zaoutsos, Stephanos P. |
| Zdroj: |
International Journal of Mechatronics and Manufacturing Systems; 2024, Vol. 17 Issue: 1 p1-20, 20p |
| Abstrakt: |
This research paper proposes a hybrid methodology that integrates experimental design, grey relational analysis (GRA), and fuzzy logic for multi-objective optimisation of laser-based processes. The aim is to optimise the laser speed and power during laser cutting to improve the surface quality and dimensional accuracy of cutting 3D-printed thin plates. The research methodology employs a systematic experimental design approach, statistical analysis, GRA and artificial intelligence model to identify the optimal process parameters and improve laser process efficiency. Integrating laser-based post-processing with additive manufacturing offers an effective solution to address the challenges of achieving high-quality products created by budget 3D printing technologies. The results of this study contribute to the development of efficient and robust hybrid manufacturing processes such as laser-based processing and 3D printing and provide valuable insights for enhancing the quality of additive manufactured parts. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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