scholarly journals Process Parameter Optimization in Fused Deposition Modeling (FDM) Using Response Surface Methodology (RSM)

Abstract The authors have requested that this preprint be withdrawn due to erroneous posting.

2020 ◽  
Author(s):  
Muhammad Salman Mustafa ◽  
Muhammad Qasim Zafar ◽  
Muhammad Arslan Muneer ◽  
Muhammad Arif ◽  
Farrukh Arsalan Siddiqui ◽  
...  

Abstract Fused Deposition Modeling (FDM) is a widely adopted additive manufacturing process to produce complex 3D structures and it is typically used in the fabrication of biodegradable materials e.g. PLA/PHA for biomedical applications. However, FDM as a fabrication process for such material needs to be optimized to enhance mechanical properties. In this study, dogbone and notched samples are printed with the FDM process to determine optimum values of printing parameters for superior mechanical properties. The effect of layer thickness, infill density, and print bed temperature on mechanical properties is investigated by applying response surface methodology (RSM). Optimum printing parameters are identified for tensile and impact strength and an empirical relation has been formulated with response surface methodology (RSM). Furthermore, the analysis of variance (ANOVA) was performed on the experimental results to determine the influence of the process parameters and their interactions. ANOVA results demonstrate that 44.7% infill density, 0.44 mm layer thickness, and 20C° printing temperatures are the optimum values of printing parameters owing to improved tensile and impact strength respectively. The experimental results were found in strong agreement with the predicted theoretical results.


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