Literature DB >> 34300927

Analysis of the Influencing Factors of FDM-Supported Positions for the Compressive Strength of Printing Components.

Zhengkai Feng1, Heng Wang1,2, Chuanjiang Wang1, Xiujuan Sun1, Shuai Zhang1.   

Abstract

Fused deposition modeling (FDM) has the advantage of being able to process complex workpieces with relatively simple operations. However, when processing complex components in a suspended state, it is necessary to add support parts to be processed and formed, which indicates an excessive dependence on support. The stress intensity of the supported positions of the printing components can be modified by changing the supporting model of the parts, their density, and their distance in relation to the Z direction in the FDM printing settings. The focus of the present work was to study the influences of these three modified factors on the stress intensity of the supporting position of the printing components. In this study, 99 sets of compression tests were carried out using a position of an FDM-supported part, and the experimental results were observed and analyzed with a 3D topographic imager. A reference experiment on the anti-pressure abilities of the printing components without support was also conducted. The experimental results clarify how the above factors can affect the anti-pressure abilities of the supporting positions of the printing components. According to the results, when the supporting density is 30% and the supporting distance in the Z direction is Z = 0.14, the compressive strength of the printing component is lowest. When the supporting density of the printing component is ≤30% and the supporting distance in the Z direction is Z ≥ 0.10, the compressive strength of printing without support is greater than that of the linear support model. Under the same conditions, the grid-support method offers the highest compressive strength.

Entities:  

Keywords:  3D printing; compression; compressive strength comparison; failure form; supporting method

Year:  2021        PMID: 34300927     DOI: 10.3390/ma14144008

Source DB:  PubMed          Journal:  Materials (Basel)        ISSN: 1996-1944            Impact factor:   3.623


  1 in total

1.  Research on Fast Recognition and Localization of an Electric Vehicle Charging Port Based on a Cluster Template Matching Algorithm.

Authors:  Pengkun Quan; Ya'nan Lou; Haoyu Lin; Zhuo Liang; Dongbo Wei; Shichun Di
Journal:  Sensors (Basel)       Date:  2022-05-09       Impact factor: 3.847

  1 in total

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