4.6 Article

Experimental analysis on density, micro-hardness, surface roughness and processing time of Acrylonitrile Butadiene Styrene (ABS) through Fused Deposition Modeling (FDM) using Box Behnken Design (BBD)

期刊

MATERIALS TODAY COMMUNICATIONS
卷 27, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.mtcomm.2021.102353

关键词

Fused Deposition Modeling; Acrylonitrile Butadiene Styrene; Box Behnken Design

向作者/读者索取更多资源

In this study, Fused Deposition Modeling (FDM) was used to process ABS polymer, with experiments revealing the significant impact of FDM input parameters such as infill percentage, layer height, and bed temperature on the density, surface roughness, and micro-hardness of ABS components. The individual and interaction effects of these parameters were observed, and a validation study was conducted to confirm the regression equation for all responses.
Fused Deposition Modeling (FDM), recently denoted by Fused Filament Fabrication (FFF), is a promising polymer processing method commonly used in the additive manufacturing domain for achieving closed dimensional tolerance. Moreover, processing on Acrylonitrile Butadiene Styrene (ABS) by FDM results in precision components manufacturing for several industrial applications. Here, an experimental attempt was conducted to find the individual and interaction effects of FDM input process parameters on ABS polymer parts. Experiments are designed based on Box Behnken Design (BBD) approach. A set of 15 experiments were carried out with varying input parameters of infill percentage (%), layer height (mu m) and bed temperature (degrees C). These input parameters of FDM shows much influence on density, processing time/printing time, surface roughness and micro-hardness of ABS coupons/samples. It was observed that the above outputs are significantly influenced by the individual and the interaction effects of process parameters. Finally, the validation study was performed to verify the regression equation for all responses.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据