Quantitative analysis of surface profile in fused deposition modelling
Source abstract
Abstract
Abstract Fused deposition modelling (FDM) is a well-known additive manufacturing technique, which can transfer digital three-dimensional (3D) models into functional components directly. Despite many advantages FDM can offer, poor surface accuracy of fabricated objects has always been a big issue that attracts increasing attention. To study the influence on the surface profiles imposed by various process parameters effectively as well as quantitatively, the mathematical model of the surface profile need to be developed. In this work, a new surface profile model is developed to characterize the surface profile of FDM fabricated parts. The process parameters are classified into two groups (i.e. pre-process parameters and fabrication process parameters) to investigate the impacts on surface characterization. Corresponding experiments are conducted using an FDM machine to make comparison with the predicted values and to validate the reliability and effectiveness of the proposed surface models. Both the experimental results and theoretical values indicate that the surface accuracy of the top surface is mainly determined by the ratio between molten paste flowrate and the nozzle feedrate under specified layer thickness and path spacing. On the other hand, the surface quality of the side surface is primarily affected by the layer thickness and the stratification angle of the surface. At the same time, some optimization approaches for the surface improvement are presented: appropriate ratio between paste flowrate and fabrication speed are required for desirable top surface and thinner layer thickness can, to some extent, alleviate the staircase effect out of the slicing procedure and the stratification angle of the side surface should be confined to a range to avoid large geometric errors.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Additive Manufacturing Materials and Processes · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (21)
Show source-provided references
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