Related Experiment Video
Updated: Jun 23, 2025
08:43
Fused Filament Fabrication FFF of Metal-Ceramic Components
Published on: January 11, 2019
17.3K
Parametric Optimization of FDM Process for PA12-CF Parts Using Integrated Response Surface Methodology, Grey
Ali Saeed Almuflih1,2, Muhammad Abas3, Imran Khan4
1Department of Industrial Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia.
Polymers
|June 19, 2024
Summary
Optimizing fused deposition modeling (FDM) parameters for PA 12-CF material using grey wolf optimization (GWO) significantly enhances surface quality and mechanical properties. This advanced method improves tensile and flexural strength while reducing surface roughness.
Area of Science:
- Additive Manufacturing
- Materials Science
- Mechanical Engineering
Background:
- Optimizing process parameters is crucial for enhancing the performance of additive manufacturing (AM) components.
- Fused Deposition Modeling (FDM) with carbon fiber-reinforced polyamide 12 (PA 12-CF) presents unique challenges in balancing multiple performance metrics.
- Key responses include average surface roughness (Ra), tensile strength (TS), and flexural strength (FS).
Purpose of the Study:
- To investigate the impact of eight key FDM parameters on the surface roughness and mechanical strength of PA 12-CF.
- To integrate Response Surface Methodology (RSM), Grey Relational Analysis (GRA), and Grey Wolf Optimization (GWO) for multi-objective optimization.
- To determine the optimal process parameters for superior material performance in FDM.
Main Methods:
- A definitive screening design (DSD) was employed for 51 experimental runs.
- Response Surface Methodology (RSM) was used to model the relationships between parameters and responses.
- Grey Relational Analysis (GRA) consolidated multiple responses into a single Grey Relational Grade (GRG), followed by Grey Wolf Optimization (GWO) for parameter optimization.
Main Results:
- Printing parameters like layer thickness, infill density, and build orientation were found to significantly influence Ra, TS, and FS.
- The integrated GRA and GWO approach successfully optimized the FDM process.
- Optimized parameters achieved a reduced average surface roughness of 4.63 μm and increased tensile and flexural strengths to 88.5 MPa and 103.12 MPa, respectively.
Conclusions:
- The Grey Wolf Optimization (GWO) method provides superior solutions compared to Grey Relational Analysis (GRA) alone.
- This integrated optimization strategy offers a systematic and robust approach for improving FDM processes.
- The findings have practical implications for reducing costs and enhancing product quality in industrial additive manufacturing applications.
